# Senior Data Engineer

**Company:** [Metriport](https://hotfix.jobs/companies/metriport)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $180k – $220k/yr
**Experience:** 6+ years
**Skills:** Spark, parquet, iceberg, Delta Lake, Snowflake, BigQuery, Redshift, AWS, S3, TypeScript, Python, Kafka, kinesis, dbt, Airflow
**Posted:** 2026-07-30

> Senior Data Engineer building and scaling clinical data pipelines, lakehouses, warehouses, and ETL/ELT systems for millions of patients to power real-time healthcare products and AI/ML workflows. Requires 6+ years data engineering experience, strong software engineering fundamentals, and mentoring skills.

## Job Description

## 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).

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