Senior Data Engineer

Responsibilities

• Raise the technical bar for our data platform: building on and improving our warehouse, data lake, and ETL/ELT architecture so it scales with patient and customer growth, and helping evaluate the right tools (batch and streaming processing, table formats, orchestration, query engines).
• Drive data projects end-to-end: writing Design Documents, shipping v0's quickly, and iterating to v1 and beyond.
• Support AI/ML efforts - making sure the AI Engineers have the data they need.
• Multiply the team: mentoring engineers on data fundamentals, reviewing designs and PRs, and judging when to invest in quality vs. ship fast.
• Participate in bi-weekly sprint planning and retros, 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:

• Scaling 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.
• Building 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

• 6+ years of engineering experience, with a heavy lean towards data engineering — building, maintaining, and scaling pipelines processing terabytes of data and millions of events a day.
• Experience across the data stack — ingestion, storage, processing, warehousing, serving — and an understanding of the tradeoffs (cost, latency, correctness, operability) at each layer.
• Experience with modern, cloud-native data stacks: e.g., Spark, open table formats (Parquet, Iceberg, Delta) on S3, and warehouses (Snowflake, BigQuery, Redshift).
• 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.

Nice-to-Haves

• Experience with streaming systems (Kafka, Kinesis), dbt, or orchestration tooling (Airflow, Dagster).
• 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).