Staff Data Engineer

What you'll be doing

We ingest clinical data for millions of patients from external healthcare sources, with continuous updates for a growing subset of those patients. You'll own the architecture and evolution of the data platform that powers our product — and ship it to customers fast.

Day to day, that looks like:

• Setting the technical direction for our data platform: evolving our warehouse, data lake, and ETL/ELT architecture to scale with patient and customer growth, and picking the right tools (batch and streaming processing, table formats, orchestration, query engines).
• Driving the critical data projects end-to-end: writing Design Documents, shipping v0's quickly, and iterating to v1 and beyond.
• Supporting AI/ML efforts: making sure the AI Engineers have the data they need.
• Multiplying the team: mentoring engineers on data fundamentals, reviewing designs and PRs, and judging when to invest in quality vs. ship fast.
• Eventually, acting as Team Lead for a group of engineers: breaking down and delegating work, unblocking teammates, and owning your team's delivery — while staying hands-on in the code.
• Driving bi-weekly sprint planning and retros, contributing to the engineering roadmap, joining our daily 30-min remote stand-up at 7:30am PST (our only mandatory meeting), and taking part in the on-call rotation.

Example projects you could own:

• Rearchitecting our patient data consolidation pipeline (deduplication, normalization, hydration) to handle 100x today's volume without 100x the cost.
• Building pipelines that deliver clinical data directly into customers' data warehouses, reliably and at scale.
• Designing the ingestion path for customers pushing large volumes of their own data into the platform.
• Building document-processing pipelines that extract structured data from PDFs, images, and free text to feed ML models.

Requirements

• 8+ years of engineering experience, with significant depth building, operating, and scaling data platforms processing terabytes of data and millions-to-billions of events a day.
• You've designed data architectures end-to-end — ingestion, storage, processing, warehousing, serving — and owned the tradeoffs (cost, latency, correctness, operability) at each layer.
• Deep experience with modern, cloud-native data stacks: e.g., Spark, open table formats (Parquet, Iceberg, Delta) on S3, warehouses (Snowflake, BigQuery, Redshift), dbt, orchestration (Airflow, Dagster), and streaming (Kafka, Kinesis). Breadth matters — you'll be picking our stack.
• Strong software engineering fundamentals — you write production code (we're a TypeScript shop, with Python in data/ML workflows), not just orchestration configs.
• Experience mentoring or guiding other engineers — through code reviews, pairing, design feedback, or onboarding.
• Located in San Francisco / Bay Area, or willing to relocate.

Bonus

• Experience leading engineers.
• Experience building or supporting ML/data science workflows (feature pipelines, model inputs/outputs, unstructured data extraction).
• Healthcare standards/technologies: FHIR, HIE, IHE, EHR/EMR, NPI, TEFCA, ADT, HL7, HEDIS, RAF, SNOMED, LOINC, ICD-10, etc.

Benefits

• Competitive equity + compensation package
• Full family Platinum health insurance, dental, and vision coverage
• 401(k) retirement plan + matching
• Flexible work from home or in-office
• Healthy lunches are complimentary when working in-office (and breakfast + dinners as needed)
• Quarterly company off-sites with the team
• MacBook provided by us
• Unlimited PTO (we work hard, but trust you to take time you need to be at your best)