We're hiring an Analytics Engineer to join the GFCO Analytics Engineering team and build the data foundations that power customer experience and compliance operations at Coinbase. You'll own end-to-end data pipelines, develop trusted metrics, and enable CX stakeholders to make faster, better decisions with clean, reliable data. This is a high-impact role where you'll directly influence how we serve and protect our customers while scaling our analytics capabilities.

What you'll do:

• Own the design, build, and maintenance of data models and pipelines that support CX operations, compliance reporting, and customer insights, ensuring data is accurate, timely, and well-documented.
• Partner with CX Operations, Compliance, and Product teams to translate business needs into data requirements and deliver self-serve analytics solutions that reduce manual effort.
• Build and maintain dashboards, metrics, and reporting tools that give CX leaders visibility into performance, customer trends, and compliance health.
• Drive data quality and governance within the CX data domain by implementing testing, monitoring, and documentation standards that ensure stakeholder trust in the data.
• Identify opportunities to automate recurring data workflows and reporting processes, shifting the team from reactive requests toward scalable, self-serve solutions.
• Collaborate with broader Data Engineering and Analytics teams to align on best practices, share learnings, and contribute to Coinbase's overall data infrastructure.

Required Skills and Experience:

• 3+ years of experience in analytics engineering, data engineering, or a related data role, with hands-on experience building and maintaining data pipelines and models.
• Proficiency in SQL and experience with modern data stack tools such as dbt, Airflow, and cloud data warehouses (Snowflake, Databricks, or similar).
• Experience with data modeling concepts (dimensional modeling, star/snowflake schemas) and building trusted, well-documented data products.
• Familiarity with BI/visualization tools (Looker, Tableau, or similar) and experience building dashboards and self-serve analytics solutions.
• Track record of partnering with non-technical stakeholders to translate business needs into data solutions, particularly in customer experience, operations, or compliance domains.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Senior Analytics Engineer

As a Senior Analytics Engineer on the Platform team, you'll build the scalable data models and pipelines that power analytics, experimentation, and decision-making across Coinbase. Our Analytics Engineering team transforms raw data into trusted, well-modeled sources that stakeholders across Product, Engineering, and Data Science rely on daily. You'll own end-to-end data solutions for specific business domains, turning complex data flows into clean, reusable frameworks that unlock commercial value at scale.

What you'll do:

• Own end-to-end data modeling for assigned business domains, from understanding source system data flows through designing modular, reusable models (star/snowflake schemas) that serve as the single source of truth for downstream teams.
• Build and optimize ETL/ELT pipelines using modern tools like dbt and Airflow, ensuring data quality, reliability, and performance at scale across Snowflake or similar warehouse architectures.
• Partner with Engineering, Product, and Data Science teams to identify data gaps, define requirements, and deliver data products that directly enable experimentation, ad hoc analysis, and business metric optimization.
• Develop scalable abstractions and frameworks (UDFs, Python packages, internal data apps) that multiply the efficiency of other data teams and reduce time-to-insight across the organization.
• Design and deliver dashboards and visualization layers using tools like Looker or Tableau, translating complex data into clear, actionable views for cross-functional stakeholders.

Required Skills and Experience:

• 5+ years in analytics engineering or data engineering with demonstrated expertise in designing modular data models and building production ETL/ELT pipelines using dbt, Airflow, or similar.
• Advanced SQL proficiency for complex transformations and query optimization, plus intermediate-to-advanced Python for scripting, automation, and building scalable frameworks (OOP experience preferred).
• Production experience with modern data warehouse architectures (Snowflake, Databricks) including performance tuning, data quality monitoring, and version-controlled development workflows (GitHub, CI/CD).
• Proven track record delivering data solutions that generated measurable business impact, with the ability to independently build domain expertise and communicate technical trade-offs to Product, Engineering, and business stakeholders.
• Experience with prompt engineering for LLMs (e.g., GPT), including designing and optimizing prompts for internal tooling and automation use cases.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

As a Senior Staff Software Engineer on the Data Platform team within Platform, you'll define and lead the technical strategy for Coinbase's data infrastructure, spanning ingestion, transformation, warehousing, streaming, and serving systems. This is a foundational role at the intersection of distributed systems, data engineering, and AI-readiness, reporting to the Senior Director of Engineering. You'll set architectural direction, drive multi-quarter roadmaps, and transition the organization from managed-service dependency toward engineering-built, platform-grade infrastructure that powers everything from fraud detection to modern multi-agent AI architectures.

What you'll do:

• Own the technical strategy and architecture for Data Platform, setting direction across data ingestion, transformation, warehousing, streaming, and serving systems while driving engineering-led cost reduction at the infrastructure layer.
• Architect data infrastructure to natively support AI and ML workloads, ensuring pipelines, data lake systems, and compute can power ML training, feature stores, real-time inference, and multi-agent AI architectures at scale.
• Drive the evolution to near-real-time data availability, enabling downstream teams across Coinbase to act on fresher data for fraud detection, financial reporting, and analytics.
• Build alignment and secure commitment from senior leadership and cross-functional partners across product, infrastructure, analytics, ML, privacy, security, and compliance on technical priorities and tradeoffs.
• Serve as the primary technical voice for Data Platform in org-wide forums including OKR planning, architecture reviews, and long-term infrastructure strategy, while elevating senior engineering talent.

Required Skills and Experience:

• 12+ years building and operating large-scale distributed data infrastructure, including streaming platforms, data lakes, batch and real-time processing engines, and query/serving layers.
• Record of owning end-to-end technical strategy and architecture for an entire data domain across multiple teams, with demonstrated success transitioning organizations from managed-service dependency toward platform-grade, engineering-built infrastructure.
• Deep systems thinking across the full data lifecycle, with ability to reason about performance, reliability, cost, security, and privacy at each layer.
• Demonstrated experience designing data systems that support ML training pipelines, feature stores, real-time inference, or AI agent workloads at scale, with familiarity across technologies such as CDC, Kafka, Databricks, Snowflake.
• Platform mindset and product-manager orientation toward data infrastructure, focused on reducing friction for developer customers and creating compounding leverage.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Job ID#: P75554