Senior Data Engineer, Data Foundations

Key Responsibilities

• Design and implement high-performance data processing and serving patterns across large-scale healthcare datasets using Spark, Python, Rust, and SQL.
• Lead complex cross-functional initiatives, balancing trade-offs across scalability, reliability, performance, cost, and delivery speed.
• Build and maintain robust data quality, validation, observability, lineage, monitoring, and alerting frameworks.
• Architect scalable Healthcare Map data products that power APIs, analytics, internal tooling, and customer-facing applications.
• Partner with Product, Data Science, and Platform teams to translate healthcare use cases into scalable technical solutions.
• Drive engineering excellence across system design, code quality, testing, documentation, and CI/CD practices.
• Mentor engineers through design reviews, technical coaching, and architectural guidance.

What you bring

• AI & ML Enablement: Experience designing data workflows, feature pipelines, or infrastructure that specifically supports AI/ML training, inference, experimentation, and monitoring.
• Data Product Engineering: Proven experience building large-scale, production-grade data products and analytical systems.
• Modern Data Systems: Strong expertise in SQL, distributed processing frameworks (e.g. Spark), cloud data platforms, and high-scale compute systems using Python and/or Rust.
• Architecture & Systems Design: Demonstrated ability to design scalable data models, platform components, and distributed system architectures.
• Analytical Rigor: Strong statistical and analytical skills; able to validate data quality and product outcomes through rigorous analysis.
• Technical Communication: Clear communicator who can explain technical decisions, trade-offs, and risks to engineers, product partners, and leadership.

Nice to have

• Healthcare Data Experience: Direct experience with claims, clinical, RWE, provider, patient, or life sciences data, including familiarity with coding systems (ICD-10, CPT, NDC, NPI).
• Data Product Delivery: Experience building and operating data products specifically designed for external consumption via customers, APIs, or serving layers.
• High-Scale Data Architecture: Proven experience in optimizing systems for performance, cost efficiency, versioning, and large-volume data productization.
• Applied AI / Agentic Workflows: Experience applying AI/agentic workflows to engineering, data quality, or delivery processes.
• Fast-Growth Execution: Experience successfully operating in high-growth or ambiguous environments where leaders must adeptly balance architecture, delivery speed, and quality.

Compensation

• San Francisco Bay Area and New York City: $176,000—$207,000 USD
• All Other US Locations: $153,000—$180,000 USD
• Eligible for performance-based bonuses, equity awards, comprehensive health/dental/vision insurance, flexible time off, 401(k) with company match, disability/life insurance.