Operations Manager, Workforce Strategy & Planning
Company Overview:
Role:
Key Responsibilities:
- Workforce Management & Capacity Planning
- Run demand forecasting and capacity planning using AI model outputs - validate projections, apply bias corrections, and translate forecasts into interval-level staffing plans. Inputs include demand trends, seasonality, product launches, and marketing activity.
- Maintain, update, and improve existing staffing models (headcount-to-volume alignment, SLA modeling, scenario planning) as inputs change - you're not building these from scratch, but you need to understand the logic well enough to adjust, improve, and defend the outputs.
- Build and distribute weekly schedules; coordinate with Team Leads on shift coverage, gaps, and real-time adjustments.
- Drive resource planning for new initiatives, including shift coverage for new channels, skill-based routing changes, and staffing implications of product or geographic launches.
- Own BPO forecast and capacity planning: translate volume projections into vendor capacity needs and flag misalignment early.
- Process contractor invoices on cadence.
- Manage schedule publishing and headcount updates.
- Operational Optimization
- Co-own the monthly Finance labor cost model review, prepare inputs, flag variances, maintain the rolling forecast.
- Work with Product, Engineering, Marketing and Support teams to stay ahead of feature rollouts and changes that will impact volume or staffing needs, as well as feed those inputs into the forecasting and planning cycle.
- Deliver hiring plan recommendations tied to volume projections, attrition trends, and batch hiring constraints.
- Track and report on OKRs: prepare leadership updates, maintain KR tracking, flag risks to targets.
- Stakeholder & System Coordination
- Serve as the primary WFM point of contact for Ops leadership, Finance, and cross-functional partners during the engagement.
- Collaborate with Data Science on predictive model refinement and operational dashboard development.
- Maintain recurring operational reporting cadences
Qualifications/Skills:
- 4+ years in workforce management, capacity planning, or workforce operations
- Experience scaling support functions in high-growth companies. You'll be operating the WFM function during a period of significant membership growth, new channel launches, and geographic expansion. Healthcare or digital health experience is a major plus.
- Strong modeling skills and comfort with large datasets. Experience with BI tools (Databricks, Looker, Tableau, or similar) are a plus - you should be able to pull data, validate assumptions, and translate analysis into actionable staffing decisions.
- Experience managing or coordinating BPO vendors: capacity planning, performance tracking, invoice reconciliation.
- Familiarity with WFM tools, helpdesk platforms (we use Intercom), and HRIS/scheduling systems (we use Rippling).
- Demonstrated ability to work cross-functionally with Finance, Marketing, Product, and Data teams.
- Strong operational reporting skills
- Comfortable stepping into an established system. You'll inherit existing models, processes, vendor relationships, and reporting cadences built by the person you're covering for.
To be a strong fit, you embody our Core Values:
- Ruthless Prioritization:
- We don’t let perfect get in the way of progress.
- We move quickly to drive value, not perfection.
- We prioritize what drives impact.
- We never compromise on standards of excellence.
- Member-First, Always:
- We design and deliver like we’re caring for someone we love.
- We create calendar, actionable, human experience.
- We prioritize responsiveness, peace of mind, and outcomes.
- We empower members with truth, clarity, and care.
- One Team, Moving Fast:
- We are aligned in purpose, prioritization, and speed.
- We gather diverse perspectives to make informed decisions.
- We clear paths for each other and move fast together.
- We communicate clearly and respectfully, rallying around shared goals.
- Radical Ownership, Relentless Execution:
- We don’t just ship– we own outcomes and drive results.
- We act with urgency and precision
- We anticipate, initiate, and follow through.
- We meet challenges with grit and pragmatism.
- We embrace new tech to deliver better outcomes.
- Mission Over Ego:
- We are ruthlessly aligned to our mission - and leave ego at the door.
- We disagree and commit.
- We don't tolerate politics or withholding information.
- We operate with honesty, transparency, and respect.
- Sustained Integrity in Every Detail:
- We earn trust by obsessing over accuracy, quality, and clarity in everything we do.
- We prioritize clinical precision - data must be right.
- We sweat the details because outcomes depend on them.
Why You'll Love Working With Us:
Data Scientist ll - Digital Intelligence
Why Socure?
Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
Job Summary:
Socure is the leading provider of digital identity verification and fraud prevention solutions, using AI and machine learning to power accurate identity trust decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.
We are seeking a Data Scientist II to join our Digital Intelligence team. In this role, you will develop machine learning features, analytical methods, and production-oriented risk signals using device, network, browser, mobile, API, session, and behavioral telemetry.
This is a hands-on role for a data scientist who can independently deliver well-scoped projects, work with complex and noisy data, and partner with engineering, product, and risk teams to improve fraud detection, identity confidence, and customer outcomes. You will deepen your expertise in Digital Intelligence while contributing to models and signals used in real-world production decisions.
Job Responsibilities:
Develop machine learning features, models, and analytical methods for device, network, browser, mobile, session, and behavioral intelligence.
Work on scoped fraud and identity risk problems where data quality, labels, telemetry coverage, and product tradeoffs need careful analysis.
Build features from large-scale, high-cardinality, sparse, noisy, and platform-dependent telemetry.
Analyze signal patterns such as spoofing, emulator behavior, automation, proxy/VPN usage, low-entropy fingerprints, telemetry gaps, and device or session fragmentation.
Design and execute validation analyses, including train/test splits, holdout checks, leakage review, drift assessment, customer impact analysis, and feature stability review.
Use supervised, unsupervised, statistical, and heuristic approaches to identify durable fraud and identity risk signals.
Investigate imperfect labels, delayed outcomes, instrumentation gaps, and changing fraud patterns to distinguish useful signal from data artifacts.
Partner with senior data scientists, engineering, product, risk, and platform teams to clarify requirements, prepare data, implement features, and support production rollout.
Contribute to model documentation, feature definitions, explainability materials, dashboards, and production-readiness reviews.
Communicate methods, assumptions, findings, limitations, and recommendations clearly to technical and cross-functional stakeholders.
Support junior data scientists and analysts through code review, analytical feedback, and sharing effective modeling and validation practices.
Job Requirements:
Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or a related quantitative field, or equivalent practical experience.
5+ years of experience in data science, applied machine learning, statistical modeling, analytics engineering, or a related technical role.
Experience building, evaluating, and improving machine learning models, features, analytical pipelines, or risk signals.
Strong SQL skills and experience working with large-scale, complex datasets.
Strong proficiency in Python and experience with data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar.
Experience with distributed data processing tools such as Spark, PySpark, Databricks, or equivalent frameworks.
Solid understanding of supervised learning, unsupervised learning, feature engineering, model evaluation, statistical validation, and experiment analysis.
Ability to work with noisy data, imperfect labels, missing values, instrumentation gaps, and changing data distributions.
Strong analytical judgment across data quality, feature design, model selection, explainability, and business impact.
Experience collaborating with engineering, product, analytics, or risk teams to move data science work toward production or operational use.
Clear communication skills, including the ability to explain technical work, assumptions, tradeoffs, and results to non-specialist stakeholders.
Ability to operate independently on defined problem areas while seeking guidance appropriately on ambiguous or high-risk decisions.
Preferred Qualifications:
Background in fraud detection, identity verification, trust and safety, anomaly detection, cybersecurity, risk modeling, or another adversarial data domain.
Experience with device intelligence, browser/mobile fingerprinting, behavioral biometrics, network intelligence, VPN/proxy detection, or telemetry signal processing.
Experience developing features from high-cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation learning.
Familiarity with production ML workflows, model monitoring, feature monitoring, or batch and near-real-time decisioning systems.
Experience with dashboarding, model explainability, feature documentation, or customer-impact analysis.
Interest in adversarial behavior, fraud patterns, telemetry quality, and applied ML systems that operate in real-world production environments.
What You’ll Gain
You will work on meaningful data science problems in fraud prevention and identity verification, using high-scale Digital Intelligence telemetry to build features and risk signals that contribute to real-world production decisions.
You will gain deeper experience with device, network, browser, mobile, session, and behavioral intelligence while working closely with senior data scientists, engineering, product, and risk partners. This role offers the opportunity to grow from independently delivering scoped modeling projects toward owning broader workstreams and developing Senior-level technical judgment over time.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
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Systems Specialist, Lifecycle Marketing
Superhuman offers a dynamic hybrid model, and candidates in this role can be based remotely. You may be expected to travel to meet in person during your team’s scheduled collaboration weeks. Managers will determine in-person time according to business needs.
This hybrid approach helps foster trust, innovation, and a strong team culture, with the flexibility of working from home, whenever you need focus time.
About Superhuman
Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company’s products include Grammarly’s writing assistance, Superhuman Docs’ collaborative workspaces, Mail’s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at superhuman.com and about our values here.
Build Love 💜:
At Superhuman, we have a deep understanding of how to build products that people love. We incorporate fun and play, infusing magic and joy to create experiences that amaze and delight. It all starts with the right team — a team that deeply cares about values, customers, and each other.
Create Massive Impact 🚀:
Our lifecycle marketing engine runs on a foundation of reliable, well-maintained systems. The data pipelines, sync configurations, and technical integrations that power our campaigns don’t manage themselves — and getting them right directly affects how we reach and retain millions of users. This role sits at that foundation, keeping it solid so the broader team can move fast and build with confidence.
The Opportunity
As Lifecycle Marketing Systems Specialist, you will serve as a technical generalist and hands-on executor within Superhuman’s Lifecycle Marketing Operations team, reporting to the Senior Manager, Marketing Systems Architecture.
This is a high-execution, detail-oriented role for someone who thrives in the weeds of martech systems — someone who finds satisfaction in keeping complex platforms running cleanly, resolving the technical friction that slows teams down, and being the connective tissue between marketing and engineering. You won’t just support programs — you’ll own the operational infrastructure that makes them possible and have the opportunity to build your own solutions leveraging the latest AI technologies. .
You’ll take on the day-to-day technical work that keeps our lifecycle systems healthy and our teams unblocked, freeing up senior capacity for strategic and product-level work.
In this role, you will:
Act as the technical backbone of the lifecycle marketing operations function, owning platform administration and day-to-day execution across martech systems
Administer and maintain Hightouch as the primary reverse ETL platform — including managing parent models, building and updating audience syncs, reviewing and approving sync requests, and ensuring sync health across destinations
Serve as the first line of support for martech systems issues, triaging problems, diagnosing root causes, and either resolving them directly or escalating with clear context to engineering
Partner with engineering and marketing teams to support technical implementations — translating requirements between stakeholders, coordinating handoffs, and helping drive work to completion
Monitor sync performance and pipeline integrity, proactively catching failures, data inconsistencies, or configuration drift before they impact campaigns
Maintain and document platform configurations, data models, and operational processes, ensuring the team has reliable references as systems evolve
Manage access, permissions, and governance across martech platforms, keeping configurations clean and auditable
Support audience segmentation and data hygiene work in partnership with Data and Lifecycle teams
Assist with QA and testing for new integrations, campaign launches, and platform changes, helping catch issues before they hit production
Identify and flag operational inefficiencies, contributing ideas for process improvement and automation opportunities
Contribute to our team’s evolution by building with AI
Qualifications
2–4 years of experience in marketing operations, marketing technology, or a related technical role
Hands-on experience with reverse ETL or data activation platforms — Hightouch or similar tools (Census, ActionIQ, etc) experience strongly preferred
Comfortable working directly with data and audiences in a warehouse-connected environment (Databricks, Snowflake, BigQuery, or similar)
Basic to intermediate SQL skills — able to read, modify, and troubleshoot queries without needing to write complex models from scratch
Strong systems thinker who can follow a data flow end-to-end and identify where things are breaking down
Able to communicate technical context clearly across engineering and marketing audiences — you know how to translate
Detail-oriented with a track record of catching issues before they become incidents
Experience with marketing automation platforms (Iterable, Braze, Marketo, or similar)
Familiarity with event streaming concepts (how data flows from product events into marketing platforms) is a plus
Comfortable in a fast-moving environment where priorities shift and ambiguity is part of the job
Bonus: Has demonstrated the ability to build solutions with AI applications like Claude
Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments
Compensation and Benefits
Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:
Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
Disability and life insurance options
401(k) and RRSP matching
Paid parental leave
20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
Annual professional development budget and opportunities
Superhuman takes a market-based approach to compensation, so base pay may vary by location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.
Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined by compensation zone and may be modified in the future.
We encourage you to apply
At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).
Senior Forward Deployed Data Engineer, Data Modernizaton
Transform healthcare with us.
At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change.
This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board.
Join us in shaping the future of healthcare.
About Forward-Deployed Engineering at QH. Data Modernization is a forward-deployed function. Every role on this team — leadership and IC alike — works directly with health system customers, on-site and in their environments, throughout the engagement. This is not a back-office data role: you'll sit with the customer's data and IT teams, present your work to their technical leadership, and be accountable for outcomes they can see. All roles are Senior/Staff level or higher.
Note on platform specialization: We are hiring Senior / Staff Data Engineers who each own deep expertise in one of our three target platforms — Databricks, Snowflake, or Microsoft Fabric. This single posting covers all three seats; we'll match you to the platform where your depth is strongest during the process. The core of the role — landing health system data in a modern lakehouse and serving as the platform-specific technical lead on an engagement — is the same across all three.
Job Summary
This is the role where the data actually moves. As a Senior Forward Deployed Engineer on the Data Modernization team, you own the platform-specific build that takes a health system from legacy connectivity — flat files, manual SFTP, a half-finished Clarity database — to a modern, AI-ready lakehouse that can serve our agentic AI workflows at full speed.
You are the deep platform expert for your stack. During an active engagement, you serve as the platform-specific technical lead under the Principal Solutions Architect: you own the ingestion, the medallion architecture, the governance configuration, and the data-sharing pattern on your platform. Between engagements, you sustain our production environments, build the accelerators and reusable IP that make the next engagement faster, support pre-sales technical discovery, and cross-train on the other platforms so the team stays flexible.
These are time-boxed, high-stakes builds. A greenfield foundation goes from zero to a live AI workflow in roughly ten weeks; an acceleration engagement folds hundreds of Clarity tables into an existing lakehouse on weeks-to-months timelines. You'll ship production-grade work in a regulated environment, where "done" means it's governed, documented, and ready to hand to the integration team — not just that the pipeline ran once.
Key Responsibilities
Work forward-deployed inside the customer's environment: partner directly with their data and IT teams, present design decisions and progress to their technical leadership, and represent QH on-site during kickoffs and key milestones
Own platform-specific architecture and build for your stack during active engagements, as technical lead under the Principal Solutions Architect
Design and implement ingestion from EHR and source systems (Epic Clarity / Caboodle, FHIR, ERP, scheduling, claims) into a medallion lakehouse
Build and harden change-data-capture, transformation, and orchestration pipelines that meet engagement timelines
Configure governance, access control, and the data-sharing pattern that hands clean, AI-ready data to QH's platform (Delta Sharing, Fabric External Sharing, Snowflake Reader Accounts, or equivalent)
Sustain production environments handed off from prior engagements, and develop reusable accelerators and IP that compress the next build
Support pre-sales technical discovery and source-data assessment alongside the Principal SA
Ensure every environment meets handoff criteria for the Client Integration team — governed, documented, reproducible
Cross-train on the other two platforms to keep the team flexible across single- and multi-engagement states
Required Qualifications
8+ years in data engineering or data platform roles, at a Senior or Staff IC level
Client-facing maturity — comfortable working on-site in a customer's environment and presenting technical work to their data and IT leadership
Deep, hands-on expertise in at least one of Databricks, Snowflake, or Microsoft Fabric (see platform note above)
Has shipped production data workloads in a regulated environment (HIPAA, HITRUST, or comparable)
Strong in Python and distributed data processing (PySpark or equivalent), plus SQL and modern transformation tooling
Comfortable as the sole platform expert on an engagement — you can own a build, not just contribute to one
Infrastructure-as-code fluency (Terraform) and CI/CD discipline (GitHub Actions)
Platform-Specific Depth (own one)
Databricks: Delta Lake, Unity Catalog, Delta Sharing, Delta Live Tables, Photon. Bonus: production Databricks experience inside a health system or Databricks partner consultancy.
Snowflake: Snowpark, Reader Accounts, Streams & Tasks, Dynamic Tables, Snowpipe, strong dbt fluency. Bonus: Epic Clarity inside Snowflake.
Microsoft Fabric: OneLake, SQL Server Mirroring for CDC, Fabric Data Factory, Fabric External Sharing, Iceberg shortcuts. Bonus: prior Azure Synapse / ADF / Databricks-on-Azure background. (The rarest and most sought-after of the three — Fabric is the newest platform.)
Ideal Experience
Resident / customer-success solutions architect or engineer from a cloud data platform vendor (Databricks, Snowflake, Microsoft FastTrack / CSU)
Senior data engineer from a health system running on your platform, or from a platform-partner consultancy
Familiarity with EHR data models and the realities of on-prem-to-cloud CDC
Background in consulting, professional services, or data platform implementation in regulated industries (healthcare strongly preferred; fintech a strong adjacent)
Desirable Skills
Ownership: You're the one person on the engagement who deeply knows this platform, and you carry that weight without needing a second set of hands on every decision.
Pragmatism: You know the difference between architecturally ideal and deliverable-in-ten-weeks, and you optimize for the latter without creating technical debt.
Reusability mindset: You build the second engagement's accelerator while delivering the first, because you've felt the cost of bespoke-everything.
Clinical-data literacy: Clarity and Caboodle don't scare you; you understand why health system data is messy and you've untangled it before.
Cross-platform curiosity: Your depth is in one stack, but you're glad to learn the other two so the team can flex across engagements.
Technical Environment
Databricks (primary), Microsoft Fabric, and Snowflake — fully platform-agnostic on acceleration engagements
PySpark and Python with type-safe patterns and modern frameworks
GitHub Actions + Terraform for CI/CD and Infrastructure as Code
Healthcare data formats including FHIR, Epic Clarity / Caboodle, and other EHR schemas
HIPAA / HITRUST-regulated cloud environments on Azure and AWS
Why Join Qualified Health?
This is an opportunity to join a fast-growing company and a world-class team that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
The work here is unusually high-leverage: every health system you modernize removes the single biggest bottleneck to deploying AI across our entire partner base. You'll be the named platform expert on real, in-flight engagements — not one engineer of fifty, but the person who owns the build.
Our employees are integral to achieving our goals, so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options, and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits
The base pay range for this role is between $180,000 and $230,000. Final offer depends on your skills, qualifications, experience, platform specialization, and location. This role is also eligible for equity, benefits, unlimited PTO.
Director, Data Modernization
Transform healthcare with us.
At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change.
This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board.
Join us in shaping the future of healthcare.
Job Summary:
The Director of Data Modernization is the technical architect and engineering leader across all of Qualified Health's data modernization engagements. You'll walk into a health system's data environment — which might be anything from a well-maintained EHR reporting database to a tangle of flat files and manual SFTP processes — and design the modern cloud data platform that will replace it.
This is the highest-leverage work on the team. Every health system you modernize from legacy connectivity to a modern data sharing pattern reduces their ongoing integration effort dramatically. You're not just building infrastructure — you're removing the single biggest bottleneck to AI deployment across our entire partner base.
You'll own the technical architecture playbook, make design decisions across concurrent engagements, lead a team of data engineers and cloud/infrastructure engineers, review all engineering output, and personally drive the most complex builds. The Engagement Manager handles the partner relationship and project management — you handle the engineering. Together, you run the engagement.
Key Responsibilities:
Own the technical architecture for modernization engagements: Azure Databricks design, data landing zones, networking, security controls
Lead and develop a team of data engineers and cloud/infrastructure engineers
Lead technical discovery and source data assessments for new engagements
Review and approve all engineering deliverables across concurrent engagements
Personally drive architecture and build for the most complex engagements
Set engineering quality standards and drive architectural decisions across the modernization practice
Maintain and evolve the technical engagement playbook
Ensure environments meet handoff criteria for the Client Integration team
Collaborate with Data Mapping Analysts on source data assessment and validation
This role requires travel to healthcare client sites for engagement kickoffs, technical discovery sessions, and key milestones. Candidates should be prepared for 15-25% travel, depending on active engagements.
Required Qualifications:
Education: Bachelor's degree in Computer Science, Engineering, or a related field. A Master's degree is preferred.
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Required Experience:
6+ years in data engineering or data platform roles, with demonstrated technical leadership
Deep Azure expertise: Databricks, ADLS2, Azure networking, managed identities, Terraform/Bicep
Experience with data platform design and deployment (greenfield builds)
Client-facing experience — comfortable leading technical conversations with health system IT teams
Preferred Skills:
Familiarity with EHR data sources and clinical data models (Epic Clarity/Caboodle preferred)
Experience with data sharing protocols (Delta Share, Fabric External Sharing, or similar)
Background in consulting, professional services, or data platform implementation
Experience designing data architectures for HIPAA-regulated environments
Track record of managing technical quality across concurrent engagements
Architectural Judgment: You can walk into an unfamiliar data environment, assess what exists, identify what's missing, and design a target state architecture that is both technically sound and achievable within a time-boxed engagement
Hands-On Leadership: You lead by example — reviewing code, pairing with engineers on tough problems, and shipping your own work alongside the team
Pragmatism: You know the difference between "architecturally ideal" and "what we can actually deliver in the engagement window" — and you optimize for the latter without creating technical debt
Client Presence: You're comfortable in a room with a health system CIO or VP of IT, explaining technical decisions in business terms
Documentation: You maintain engagement playbooks and architecture patterns so the next engagement benefits from what you learned in the last one
Technical Environment:
Our data infrastructure is built on modern cloud technologies including:
Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
PySpark for distributed data processing
GitHub Actions + Terraform for CI/CD and Infrastructure as Code
Python with type-safe patterns and modern frameworks
Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
Why Join Qualified Health?
This is an opportunity to join a fast-growing company and a world-class team, that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits: The pay range for this role is between $165,000 and $200,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
Staff / Principal Forward-Deployed Architect, Data Modernization
Transform healthcare with us.
At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change.
This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board.
Join us in shaping the future of healthcare.
Job Summary
The Staff / Principal Forward-Deployed Architect is the senior-most technologist in our Data Modernization Services function — and the single named architect across every engagement we run. You own the reference architecture that defines how we land an EHR-anchored, AI-ready data foundation on Databricks, Snowflake, and Microsoft Fabric, and you stay close enough to the work to ship code yourself when an engagement calls for it.
The work is unusually high-leverage. Every health system we modernize — from legacy reporting databases and SFTP-driven feeds to a modern lakehouse with Delta Sharing, Reader Accounts, or Fabric External Sharing — collapses the path from "data exists somewhere" to "agentic AI workflows can safely run against it." You're the person who decides what that target state looks like, defends those choices in front of a customer CTO, and then leads the team that builds it on a 10-week greenfield clock.
You'll lead a tight bench of platform-specialist Senior Data Engineers (one each on Databricks, Snowflake, and Fabric) plus a Cloud/Platform Engineer. You're the public face of the practice in pre-sales discovery — and during active delivery, you're the engagement-embedded tech lead. Strong opinions, loosely held. Equally comfortable in a CTO conversation and a Terraform repo.
This posting spans both Staff and Principal levels; the offer level is calibrated to depth of experience and breadth of demonstrated technical leadership.
Key Responsibilities
Own the cross-platform reference architecture for the Modern Data Platform across Databricks, Snowflake, and Fabric — and evolve it as platforms and partners change
Serve as the engagement-embedded tech lead on the active engagement: architecture, design reviews, and hands-on build on the hardest parts
Lead technical discovery with prospective health system partners — assess source environments (Epic Clarity/Caboodle, Cogito on Cloud, Bulk FHIR, flat-file SFTP) and design a defensible target state
Lead and develop a team of platform-specialist Senior Data Engineers and a Cloud/Platform Engineer; set the technical bar
Review and approve all engineering deliverables — IaC, ingestion patterns, data sharing topology, security controls
Partner with the Engagement Manager and Field CDO to scope SOWs, defend timelines, and surface technical risk before it becomes schedule risk
Coordinate technical handoffs to the QH Platform team via Delta Sharing / Reader Account so AI workflows can be deployed against the modernized foundation
Maintain the technical engagement playbook and a library of accelerators so each engagement starts further along than the last
Carry the technical narrative in pre-sales: present to CTOs, CDOs, and enterprise architects; convert technical credibility into signed work
Required Qualifications
Education: Bachelor's degree in Computer Science, Engineering, or a related field. Master's preferred.
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Required Experience:
10+ years in data engineering, data platform architecture, or solutions architecture roles, with demonstrated technical leadership of multi-person teams
Hands-on production experience across at least two of Databricks, Snowflake, and Microsoft Fabric — and the technical curiosity and pattern-recognition to credibly own the third
Three or more enterprise lakehouse / cloud data platform implementations delivered in regulated industries
Deep cloud fluency, with Azure as the most common engagement substrate: networking, identity, key management, IaC (Terraform or Bicep), and observability
Client-facing experience leading executive technical conversations — comfortable in a room with a health system CTO, CDO, or CISO
Ideal Experience
Healthcare data fluency: Epic Clarity / Caboodle, Cogito on Cloud, Bulk FHIR, HL7, claims data, and the realities of on-prem-to-cloud CDC
Direct experience with modern data sharing patterns: Delta Sharing, Snowflake Reader Accounts, Fabric External Sharing, Iceberg shortcuts
HIPAA / HITRUST-regulated environments; opinions on PHI segmentation, BAA scope, and audit posture
Background in a Databricks / Snowflake / Microsoft Fabric professional services or field engineering org, a healthcare-focused consultancy, or a large IDN data platform team
Track record of architecting under a time-boxed engagement (e.g., 8–10 week greenfield delivery) rather than open-ended programs
Desirable Skills
Multi-Platform Judgment: You don't get religious about Databricks vs Snowflake vs Fabric. You can articulate when each is the right call for a given customer's data gravity, existing investments, and roadmap — and design accordingly
Architect Who Still Builds: You lead by example. You review IaC and PySpark, you pair on the hardest design problems, and you'll personally drive the build on the gnarliest part of an engagement instead of throwing it over the wall
Pragmatism: You know the difference between the architecturally ideal target and what a 10-week engagement can realistically land — and you optimize for delivered value without quietly accumulating technical debt
Pre-Sales Presence: You can walk into a discovery session cold, ask the right five questions, and leave with a credible architectural sketch. You convert technical depth into customer confidence
Strong Opinions, Loosely Held: You bring a point of view to every architecture review, defend it well, and update it cleanly when the customer environment or new information argues against you
Documentation Discipline: You treat the playbook as a product. Every engagement leaves behind patterns, accelerators, and decisions the next engagement inherits
Travel Requirements
This role requires travel to healthcare client sites for engagement kickoffs, technical discovery sessions, on-site working weeks, and key milestones. Candidates should be prepared for 25–35% travel, depending on active engagements and pre-sales pipeline.
Why Join Qualified Health?
This is an opportunity to join a fast-growing company and a world-class team that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
This role specifically is one of the highest-leverage technical seats in the company. You're not maintaining one platform — you're defining how an entire generation of health systems gets onto a modern, AI-ready data foundation. Every engagement you architect compounds across our partner base.
Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits
The pay range for this role is between $190,000 and $250,000, and will depend on your skills, qualifications, and experience. This role is also eligible for equity and benefits.
Staff Software Engineer, Backend
About Us:
Role:
Key Responsibilities:
- Contribute to the design, development, and scaling of core data infrastructure using GCP, Spark, Databricks, and Fivetran.
- Develop robust and maintainable ETL/ELT workflows that support diverse structured and unstructured data needs across the organization.
- Implement and manage Change Data Capture (CDC) pipelines to enable near real-time data replication and synchronization.
- Define and enforce data governance and compliance standards, including access control, auditability, lineage, and metadata management.
- Build and manage streaming and batch data pipelines to serve high-impact use cases across analytics, product, compliance, and experimentation.
- Act as a strategic partner to cross-functional teams (product, analytics, engineering, clinical) to ensure data is accessible, trustworthy, and impactful.
- Drive the long-term architectural vision of our data platform to support current and future business and product needs.
Qualifications/Skills:
- 5+ years of experience in software engineering, with a focus on scalable data architectures.
- Strong expertise in GCP (IAM, GCS, Pub/Sub, etc.) and hands-on experience with Spark and Databricks.
- Hands-on experience with CDC technologies like Fivetran, or equivalent.
- Proficiency in ETL/ELT tools and frameworks (dbt, Apache Airflow, Dataform, etc.).
- Deep understanding of data governance principles, including compliance and security best practices.
- Demonstrated success in collaborating across functions to deliver data solutions for analytics, experimentation, or compliance.
- A balance of IC execution and leadership skills; you’re equally comfortable rolling up your sleeves or mentoring others.
- Familiarity with streaming data architecture, real-time ingestion, and delivery frameworks.
- Proficient in SQL and Python for data processing and automation.
- Strong problem-solving skills with the ability to work in a fast-paced environment.
- Excellent communication and technical storytelling skills — you can align technical work with business value.
Nice-to-Have Skills and Experiences:
- Experience with Terraform or Infrastructure-as-Code (IaC) for data infrastructure automation.
- Background in HIPAA or other regulated environments with sensitivity to data privacy and compliance.
- Familiarity with the dbt Semantic Layer and modern data modeling best practices.
- Exposure to data observability platforms and practices.
- Familiarity with machine learning data pipelines.
- Exposure to multi-cloud or hybrid-cloud environments.
- Experience building scalable solutions in a 0-1 environment.
To be a strong fit, you also need:
- Bias Toward Action: Demonstrated ability to take initiative, make decisions under uncertainty, and move projects forward even in the face of ambiguity. We value individuals who are self-starters and ready to act on opportunities and challenges alike.
- Entrepreneurial Spirit: Strong adaptability to changing business needs with a knack for building and optimizing processes. Your entrepreneurial mindset will be crucial in navigating the dynamic landscape of our industry, ensuring our platform remains competitive and responsive to user needs.
- Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders. Effective communication is vital for cross-functional collaboration and ensuring alignment across our organization.
- Remote Work Adaptability: Comfort with remote work environments, demonstrating the ability to stay productive and connected with the team irrespective of physical location.
- Continuous Improvement: A willingness to question assumptions and a commitment to continuous improvement. Your openness to feedback and dedication to personal and professional growth will contribute significantly to our collective success.
Forward Deployed Engineer
Transform healthcare with us.
At Qualified Health, we’re redefining what’s possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring—working alongside leading health systems to drive real change.
This is more than just a job. It’s an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you’re ambitious, innovative, and ready to move fast, we’d love to have you on board.
Join us in shaping the future of healthcare.
Job Summary:
Qualified Health is seeking a Forward Deployed Engineer to serve as a technical implementation specialist and forward-deployed consultant for our healthcare data integration and AI initiatives. This is a fast-paced, high-ownership role for someone who thrives in dynamic environments, takes initiative, and drives outcomes without waiting to be told what to do next.
In this hands-on consulting role, you’ll design and build robust data pipelines that transform raw healthcare data from diverse sources (Epic, LIMS, PACS, SharePoint, etc.) into production-ready datasets powering our AI platform—while also acting as a trusted technical advisor to our health system partners. You will leverage AI-assisted code development to accelerate delivery and set a new standard for what’s possible at the intersection of healthcare data and artificial intelligence.
We are looking for critical thinkers who can independently diagnose ambiguous problems, architect creative solutions, and communicate technical findings clearly to both technical and non-technical audiences. You must be comfortable operating with a consultant’s mindset—adapting quickly to new partner environments, earning trust through quality of work, and delivering results under tight timelines.
You own: Technical implementation, ETL development, data quality validation, pipeline construction, troubleshooting, and production deployment execution, and partner-facing technical consulting
Manager owns: Partner relationships, requirements gathering, timeline management, stakeholder communication, issue escalation, and ensuring delivery meets expectations
Together you deliver: Successful data integrations that meet partner needs on time with high quality
This is a technical role for someone who loves working with data, enjoys solving puzzles, and takes pride in building reliable, production-grade solutions.
Key Responsibilities:
Technical Implementation & Development
Design and build ETL pipelines using PySpark, SQL, and Azure data services to process healthcare data from multiple source systems
Execute data extraction and transformation operations on complex healthcare datasets, ensuring accuracy and compliance with established standards
Develop data quality validation frameworks to identify and resolve issues during integration, QC, and backtesting phases
Troubleshoot technical issues including data schema mismatches, transformation logic errors, and performance bottlenecks -- independently diagnosing root causes and driving resolution
Build reusable data components and standardized integration patterns that accelerate future implementations
Optimize pipeline performance for large-scale healthcare datasets, ensuring efficient processing and resource utilization
Implement data validation rules specific to healthcare contexts (e.g., clinical code validation, temporal logic checks, referential integrity)
Write and maintain technical documentation for data pipelines, transformations, and integration patterns
Support production deployments by coordinating with infrastructure teams and conducting final testing
Leverage AI-assisted code development tools to accelerate delivery and improve solution quality
Client Consulting & Collaboration
Serve as a trusted technical advisor to health system partners, translating complex data and AI concepts into clear, actionable guidance
Partner with Data Integration Manager to translate partner requirements into precise technical specifications
Participate in technical discussions with partner IT teams to understand data schemas, access methods, and integration constraints
Provide expert guidance on data mapping specifications, transformation approaches and architecture decisions
Identify data quality issues and work with Manager to coordinate resolution with partners
Communicate technical findings from QC and backtesting clearly to both technical and non-technical stakeholders
Adapt consulting approach and communication style to the culture and maturity of each partner enviornment
Contribute to continuous improvement of tools, processes, and technical standards
Product Prototyping & Innovation
Support rapid prototyping of new AI-powered product features and data capabilities in close collaboration with product and engineering teams
Translate partner use cases and field insights into prototype solutions that demonstrate the potential of the Qualified Health platform
Build and iterate on proof-of-concept integrations and analytical tools to test new approaches before full-scale implementation
Leverage AI-assisted development practices to compress prototyping cycles and explore solutions at speed
Document learnings and outcomes from prototyping efforts to inform product roadmap decisions and reusable patterns
Bring a builder’s mindset to ambiguous problem spaces, moving quickly from idea to working demonstration
Required Qualifications:
5+ years of experience in data analytics, data engineering, or solution delivery roles, with demonstrated expertise in data integration and ETL processes
Strong analytical toolkit with proficiency in:
PySpark for distributed data processing
Advanced SQL for data querying and transformation
Excel for data analysis and reporting
Production ETL experience: Track record of building and maintaining production-grade data pipelines with proper error handling and monitoring
Data quality focus: Experience implementing validation frameworks and troubleshooting data quality issues
Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake
Consultant mindset: ability to earn trust quickly, communicate complex ideas to diverse audiences, and deliver value in client-facing environments
Ownership Mentality: takes full accountability for the quality and outcome of your work from scoping through production
Attention to detail: Commitment to accuracy, testing, and delivering reliable solutions
Collaborative working style: Comfortable partnering with non-technical colleagues and adapting to feedback
Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field
Preferred Skills:
Epic Clarity experience: Direct work with Epic's relational database structure and clinical data models
Healthcare data experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data)
Healthcare data standards knowledge: Understanding of FHIR, HL7v2, DICOM, LOINC, SNOMED, ICD-10
Healthcare compliance awareness: Understanding of HIPAA requirements and healthcare data security best practices
Data warehouse/lakehouse experience: Familiarity with dimensional modeling and modern data architecture patterns
DevOps practices: Experience with Git, CI/CD pipelines, and infrastructure-as-code
Performance tuning: Proven ability to optimize complex data transformations for scale
LIMS/PACS experience: Prior work integrating laboratory or imaging systems data
Multiple data format fluency: Experience with JSON, XML, Parquet, CSV, and other healthcare interchange formats
Experience with AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate coding and prototyping
Prior experience in a client-facing technical consulting, forward deployment, or solutions engineering role
Technical Environment:
Our data infrastructure is built on modern cloud technologies including:
Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
PySpark for distributed data processing
GitHub Actions + Terraform for CI/CD and Infrastructure as Code
Python with type-safe patterns and modern frameworks
AI-assisted development tooling for accelerated engineering
Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
What Success Looks Like:
High-quality data pipelines delivered on schedule with thorough testing and documentation
Proactive issue identification with technical problems caught and resolved before impacting partners
Reusable components that reduce implementation time for subsequent integrations
Clean production deployments with minimal post-launch issues
Technical credibility with partner IT teams based on quality of work
Efficient troubleshooting with quick diagnosis and resolution of data quality issues
Impact & Growth Opportunity:
As a Forward Deployed Engineer at Qualified Health, you'll build the data infrastructure that powers AI-driven insights for major health systems. Your work directly enables better patient care by ensuring high-quality, reliable data flows into clinical decision support tools. This role offers deep technical learning in healthcare data, exposure to diverse health system architectures, and growth potential into senior technical or platform architecture roles as we scale.
Why Join Qualified Health?
This is an opportunity to join a fast-growing company and a world-class team, that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits: The pay range for this role is between $140,000 and $200,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
Engagement Manager, Data Modernization
Transform healthcare with us.
At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change.
This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board.
Join us in shaping the future of healthcare.
Job Summary:
The Engagement Manager for Data Modernization owns the delivery lifecycle for one of the most strategically important initiatives at Qualified Health. Many of our 15+ health system partners are still running legacy data infrastructure that creates significant slowdowns in AI deployment. You'll lead the engagements that change that — helping partners stand up modern Azure Databricks environments, land their EHR and source system data in a cloud-native architecture, and unlock the ability to deploy our agentic AI workflows at full speed.
You are the single point of accountability for each engagement — from scoping and SOW alignment through milestone delivery and handoff to our integration team. You'll run the weekly status calls, manage partner expectations, coordinate across engineering, mapping, and infrastructure resources, and ensure every engagement delivers on its promises.
This is not a traditional PMO role. You'll be managing deeply technical engagements where the deliverable is a functioning data platform. You need enough technical fluency to understand what's happening at the infrastructure and data layer, ask the right questions, and spot risks before they become blockers — all while maintaining the partner relationship and keeping the project on track.
Key Responsibilities:
Own the modernization engagement lifecycle: scoping, SOW alignment, kickoff, milestone tracking, status reporting, and handoff
Serve as primary point of contact for partner stakeholders during engagements
Coordinate across engineering, data mapping, cloud/infrastructure, and client integration resources
Manage engagement timelines, risks, and dependencies across 2-3 concurrent engagements
Run weekly status calls with partner teams
Ensure clean handoff to the Client Integration team post-modernization
Build and refine the engagement playbook for repeatability and scalability
Track capacity across concurrent engagements and flag resource conflicts early
Required Qualifications:
Bachelor's degree in Engineering, Business, Information Technology, or a related field
4-7 years in technical project/program management, professional services delivery, or technical consulting
Experience managing data platform, cloud infrastructure, or data integration projects
Sufficient technical fluency to engage in conversations about Azure, Databricks, data pipelines, and networking
Strong communication skills: clear status reporting, expectation management, risk escalation
Ability to travel for engagement kickoffs, key milestones and on-site working sessions 20-30% of the time
Preferred Skills:
Healthcare IT or health system experience — understanding of how health systems operate, their procurement and IT decision-making dynamics
Experience managing concurrent engagements (2-3 at a time) with different partners and timelines
Background in a consulting firm, systems integrator, or professional services organization
Experience building engagement playbooks and delivery processes from scratch
Partner Management: You know how to manage expectations, deliver difficult messages when timelines shift, and maintain trust even when things get complicated
Technical Fluency: You can't write the Terraform, but you understand what it does and you can tell when a technical conversation is going sideways
Organizational Rigor: You manage milestones, action items, and resource allocation across concurrent engagements without dropping anything
Process Building: You're excited by the opportunity to build the engagement playbook, not just follow one — because the playbook doesn't fully exist yet
Adaptability: Comfort working in a startup where your role will evolve as the data modernization service line matures
Technical Environment:
Our data infrastructure is built on modern cloud technologies including:
Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
PySpark for distributed data processing
GitHub Actions + Terraform for CI/CD and Infrastructure as Code
Python with type-safe patterns and modern frameworks
Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
Why Join Qualified Health?
This is an opportunity to join a fast-growing company and a world-class team, that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits: The pay range for this role is between $130,000 and $165,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
Director, Forward Deployed Engineering
Transform healthcare with us.
At Qualified Health, we’re redefining what’s possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring—working alongside leading health systems to drive real change.
This is more than just a job. It’s an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you’re ambitious, innovative, and ready to move fast, we’d love to have you on board.
Join us in shaping the future of healthcare.
Job Summary:
Qualified Health is seeking a Director of Forward Deployed Engineering to own the end-to-end data relationship with some of the most prestigious health systems in the country. In this fast-paced, high-ownership role, you will lead a pod of Healthcare AI Solutions Engineers—forward-deployed consultants who design, build, and operate the data infrastructure powering our AI-driven clinical and operational workflows.
Your pipelines don’t just move data—they directly enable AI systems that help clinicians make better decisions for their patients. As the leader of this team, you are accountable for delivery quality, partner satisfaction, and the professional growth of every engineer in your pod. You’ll leverage AI-assisted development practices to drive speed and quality, and you’ll set the standard for what’s possible at the intersection of healthcare data and artificial intelligence.
This role demands executive-level judgment, deep technical credibility, and the consultant’s ability to earn trust quickly and adapt across complex partner environments. You take ownership, think critically, and solve problems independently—while empowering your team to do the same.
Key Responsibilities
Own the end-to-end data integration for 2–4 health system partners—from initial onboarding through live production operations—with full accountability for delivery timelines and partner satisfaction
Lead a pod of 2–3 Forward Deployed Engineers, mentoring and developing forward-deployed consultants while delivering against tight partner timelines (initial rollout target: <90 days from kickoff)
Serve as the primary technical relationship owner for your partners’ data and IT teams—running orientation calls, scoping sessions, and executive check-ins at the CTO/CMIO level, and bringing a consultant’s ability to communicate complex technical decisions to senior stakeholders
Design and build data pipelines that ingest Epic Clarity data, transform it through FHIR standards, and deliver AI-ready datasets via Delta Lake and Delta Sharing—the foundation for everything the product does; leverage AI-assisted development tooling to accelerate delivery and improve quality
Collaborate with the Product, AI Engineering and Data Science teams to scope new workflow data requirements, support product prototyping initiatives, and ensure pipeline outputs support backtesting, production inference, and evaluation
Drive continuous improvement of integration patterns, tooling, and technical standards—building reusable components that accelerate future deployments and raise the quality bar across the team
Required Qualifications:
7+ years as a data engineer or engineering leader, with experience building production data pipelines, leading technical teams, and owning client relationships end-to-end
Strong expertise in Epic Clarity/Caboodle data models—you know your way around the clinical tables that power healthcare AI
Proficiency with Databricks (PySpark, Delta Lake), SQL Server, and Azure cloud services (ADLS, Key Vault, ADF)
Experience with FHIR/HL7 healthcare interoperability standards and data transformation patterns
Executive-level client-facing communication—you can present data architecture decisions to a health system CTO, scope a new workflow with a CMIO, and debug a complex SQL query in the same day
Consultant mindset: the ability to earn partner trust quickly, adapt to new environments, and deliver high-quality outcomes under tight timelines
Data quality obsession—you build validation frameworks and monitoring, not just pipelines; you catch problems before the partner does
Ownership mentality: takes full accountability for team delivery, partner outcomes, and technical quality from scoping through production
Critical thinking: applies structured reasoning to evaluate options, anticipate risks, and make sound decisions independently under uncertainty
Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field
Preferred Skills:
Experience with healthcare data from multiple EHR vendors (Epic, Cerner, eCW, athenahealth, NextGen)
Terraform or infrastructure-as-code experience for tenant provisioning
Background in healthcare consulting, EHR implementation, forward deployment, or health system IT
Experience with real-time data processing (HL7 feeds, FHIR subscriptions, streaming pipelines)
Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate engineering and prototyping
Prior experience managing or mentoring forward-deployed engineers or technical consultants
Technical Environment:
Our data infrastructure is built on modern cloud technologies including:
Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
PySpark for distributed data processing
GitHub Actions + Terraform for CI/CD and Infrastructure as Code
Python with type-safe patterns and modern frameworks
Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
What Success Looks Like:
High-quality data pipelines delivered on schedule with thorough testing and documentation
Proactive issue identification with technical problems caught and resolved before impacting partners
Reusable components that reduce implementation time for subsequent integrations
Clean production deployments with minimal post-launch issues
Technical credibility with partner IT teams based on quality of work and consulting prescence
A high-performing pod of Healthcare AI Solutions Engineers who grow under your leadership and consistently deliver partner outcomes.
Impact & Growth Opportunity:
As a Director, Forward Deployed Engineering at Qualified Health, you'll build the data infrastructure that powers AI-driven insights for major health systems. Your work directly enables better patient care by ensuring high-quality, reliable data flows into clinical decision support tools. This role offers deep technical learning in healthcare data, exposure to diverse health system architectures, and growth potential into senior technical or platform architecture roles as we scale.
Why Join Qualified Health?
Mission that matters: We partner with the country's leading health systems to safely deploy AI that improves patient care, operational efficiency, and financial performance. Your work directly impacts clinical outcomes for millions of patients.
Serious traction: 14+ health system partners including the University of Texas system, University of Rochester Medical Center and Jefferson Health — scaling to 100K+ users.
Public Benefit Corporation: We're organized to prioritize patient outcomes alongside business performance. This isn't lip service — it's in our charter.
Comp that competes: We offer market competitive base salary, meaningful equity with real upside, and comprehensive benefits. We are happy to offer flexible working hours and an inclusive environment that fosters creativity and innovation,
Our Commitment to Diversity
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits: The pay range for this role is between $185,000 and $225,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
The full posting opens here — pay, setting and the full description, without leaving the list.