About the Team & Role

The Quality Intelligence team sits at the vital intersection of data, AI, and manufacturing quality at Anduril. We empower our factory floors through three distinct pillars: Analytics, Manufacturing AI, and Vision Inspection.

As a Quality Specialist within Quality Intelligence, you will own the end-to-end data and analytics products that directly impact our production lines, hardware quality engineers, and program leaders. Rather than sitting in a siloed back office, you will operate in a hub-and-spoke model. While HQ builds platform-grade analytics centrally, you will be the boots on the ground in Atlanta—partnering directly with the site's applications lead to localize, run, and scale the analytics our production floor depends on. 

We build scorecards that catch quality drift before customers do, construct data pipelines that turn raw ERP/MES/QMS data into operational decisions, and deploy AI tools that compress hours of manual triage into minutes. 

This position is based at our Atlanta, GA facility and requires up to 25% travel to other Anduril sites and key vendors.

What You’ll Do

• Operate at the Intersection of Hardware & Data: Spend time on the shop floor to deeply understand quality workflows. You will translate physical manufacturing processes into well-designed, actionable digital dashboards and analytics tools.
• Own Atlanta's Analytics Architecture: Design, build, and operate the production scorecards, Piece Part Plan pipelines, and inspection-data analytics that run the Atlanta facility. Your local decisions will set the design patterns for other Anduril sites.
• Wrangle Production Data: Pull from diverse hardware production systems (ERP, MES, QMS, inventory), build robust pipelines and ontologies in Palantir Foundry and Databricks, and partner with ML practitioners to ship analytics products operators rely on.
• Investigate Data Quality at the Root: When a dashboard is inaccurate or a metric looks off, you are the lead investigator. You will run deep-dive analyses in SQL and Python, trace anomalies back through the technical stack, identify root causes, and fix them at the source.
• Drive Technical Rigor: Implement automated data-quality checks, validation rules, and monitoring directly into our pipelines to ensure our quality data is provably trustworthy.
• Lead Data Projects End-to-End: Partner cross-functionally with program quality leads and manufacturing engineers from initial requirements gathering to final deployment.
• Build AI-Assisted Workflows: Develop small applications and automated workflows in Foundry Workshop / AIP that reduce repetitive analyst work by 10x.
• Leverage AI Aggressively: We expect you to use AI tools (Cursor, Claude Code, Copilot, AIP) to draft pipelines, write tests, generate dashboards, and accelerate the repetitive parts of your day-to-day workflow.

Required Qualifications

• Education: Bachelor’s degree in Computer Science, Mechanical Engineering, Industrial Engineering, or a related technical field from an accredited engineering program.
• Experience: 4+ years in a Data Engineer, Analytics Engineer, or similar role, with at least 2 years of applied data engineering experience directly within a manufacturing or hardware product engineering environment.
• Domain Knowledge: A strong understanding of manufacturing workflows, quality gates, and how shop-floor data impacts product quality. Comfort working directly on active production floors.
• Data Tooling: Production experience building and maintaining data pipelines in Palantir Foundry, Databricks, or an equivalent cloud lakehouse.
• Advanced SQL & Python: Strong SQL skills for handling large, multi-source datasets (heterogeneous system joins, window functions, query tuning) and Python for data transformation (Pandas, PySpark, etc.).
• AI Tooling Competency: Demonstrated experience utilizing modern AI coding tools with the critical-thinking ability to review and debug AI-generated outputs.
• Problem Solving: Proven capability to perform root-cause analysis on complex data issues.
• Communication: Ability to communicate plainly and effectively—translating complex data insights to a director without using jargon, and to an engineer without losing technical precision.
• Security Clearance: Must be eligible to obtain and maintain a U.S. Government security clearance (this role is subject to ITAR).

Preferred Qualifications

• Experience supporting analytics for hardware manufacturing (New Product Introduction (NPI), production ramp, or high-volume manufacturing) across systems like ERP (Oracle, NetSuite, SAP), MES, QMS, PLM (Teamcenter), or inventory management systems.
• Familiarity with hardware quality methodologies: RCCA / 8D, FMEA, GD&T, IQC / OQC, and control-plan design.
• Experience working in defense or highly regulated manufacturing environments (ITAR, AS9100, IPC-610, MIL-STD-1916, or similar).
• Adherence to software engineering best practices: Git, code reviews, continuous integration (CI), and testing data code with the same rigor as application code.
• Experience integrating Large Language Models (LLMs) or Machine Learning models into operational workflows (e.g., RAG over operational data, AI-assisted triage, or agentic data exploration).

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the Team

Every business running on Stripe eventually asks the same questions: What's happening with my business? What does it mean for my company? How do I reconcile my books? And how do I get my Stripe data into my own systems and apps? This is all becoming even more important in the era of AI, where merchant’s agents need the right access to, and understanding of, Stripe’s data. 

The Data Products team exists to answer those questions — at any scale, for any business. We build the products that turn Stripe's rich transaction data into understanding and action: Sigma for deep SQL-powered analytics, Stripe Data Pipeline for delivering Stripe data directly into merchants' own warehouses and applications, and databases for surfacing the right insight, in context, right inside the Dashboard.

Our users range from a founder running their first revenue report to an enterprise finance team reconciling millions of transactions across dozens of markets, to any agent working on a merchant’s behalf. What they all share is a need to trust their data, understand their business, and move fast. We make that possible.

About the Role

As the PM leading Data Products, you will own the product strategy and execution for Stripe's merchant-facing data portfolio — defining what it means for Stripe to be the best data platform for our merchants and agents. You'll set the direction across Sigma, SDP, and other data products, lead a team of PMs, and work closely with engineering, design, sales, and Stripe customers to shape how businesses access, analyze, and act on their Stripe data.

This is a high-stakes, high-visibility role. Data access is increasingly a core buying criterion for Stripe's largest customers, and the competitive landscape for data portability and embedded analytics is evolving fast. You'll need to think strategically about platform positioning, lead through ambiguity, and ship products that work flawlessly for a very sophisticated user base.

What You'll Do

• Set and own the product strategy for Stripe’s data products, defining the multi-year vision and translating it into a coherent roadmap that balances enterprise growth, self-serve expansion, and platform quality
• Lead and develop a PM team. Manage, mentor, and hire PMs; build a high-caliber team culture with strong product craft and clear ownership
• Drive revenue and retention outcomes. Deeply understand the commercial role of data products in Stripe's sales and self serve motions and build accordingly
• Define what "great" looks like for merchant data access — from schema design and query performance to delivery reliability, latency SLAs, and integrations with third-party warehouses (Snowflake, BigQuery, Redshift, Databricks)
• Partner with enterprise customers. Engage directly with Stripe's largest users to understand how they use and rely on their Stripe data, and feed those insights back into the roadmap
• Navigate deep technical complexity. Work fluently with data engineering and infrastructure teams on the underlying Reporting Data Warehouse and data pipeline architecture
• Anticipate the AI shift. Identify how AI-native workflows (agentic data access, natural language querying, automated reporting) should reshape the product surface over the next 2–3 years
• Communicate and influence broadly. Write crisp strategy docs, earn trust from senior stakeholders across Product, Sales, and Finance, and represent Data Products clearly at the leadership level

Who You Are

• 10+ years in product management, including experience leading or managing PM teams of 5+ PMs
• Deep expertise in data products. You have shipped at least one of: a BI/analytics tool, a data integration product, a warehouse connector, or a developer data API
• Strong commercial intuition. You understand how data products drive enterprise deal velocity, expansion, and retention, and you've worked closely with Sales and CS on product strategy
• Technically fluent. You can hold your own in discussions about data pipeline architecture, warehouse connectors, SQL query execution, and data delivery semantics; you don't need to write the code but you need to understand the tradeoffs
• Exceptional written communicator. You write with the clarity and precision Stripe's culture demands, from a tight decision memo to a multi-year strategy narrative
• High ownership instincts. You proactively identify what needs to happen, move fast without waiting for permission, and hold yourself accountable to outcomes
• Comfortable in a complex stakeholder environment. Data products touch engineering, enterprise sales, customer success, finance, and legal; you can align them without losing pace

Nice to Have

• Experience building products on top of or integrating with major cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)
• Familiarity with Stripe's data model and the kinds of analytics questions merchants care about (payments, disputes, revenue recognition, reconciliation)
• Background in fintech or payments — you understand the data complexity that comes with operating across hundreds of payment methods, currencies, and regulatory regimes

Why This Role

Stripe's merchants run their businesses on Stripe data. When Stripe’s data products surface the right insight at the right moment — merchants make better decisions, and they stay on Stripe. This role is a direct lever on that outcome. You'll have meaningful scope, a strong team, and the opportunity to define what world-class data access looks like for the most important businesses in the world.