Staff Data Engineer

Staff Data EngineerMetriport is an open-source data intelligence platform that helps healthcare organizations access and exchange patient data in real-time: record retrieval that used to take days now takes seconds, and clinicians walk into every appointment with the full patient picture. We integrate with all major US healthcare IT systems and tap into comprehensive medical data for 300+ million individuals.We've found product-market fit with multi-million ARR, 100+ customers (including Amazon One Medical, Strive Health, Circle Medical, and Brightside Health), backing from top VCs, and years of runway. We're ready to scale. We're a tight-knit, high-performing team of mostly former founders (including two YC alumni). We're engineering-heavy, operate with minimal bureaucracy and high autonomy, and hire based on competence, not prestige. We push hard—founders work six days a week from our SF office—but give everyone freedom to craft their schedule. We measure output and we're committed to sustainable intensity.About YouWe're looking for a data engineering leader who can own our data platform end-to-end:You've designed and operated data platforms at scale, with broad hands-on experience across the ecosystem — distributed processing, lakehouses, warehouses, streaming, orchestration — and people usually come to you for technical guidance.You've led engineers before — as a team lead, tech lead, or founder — and you own outcomes: technical direction, results, and the work of the people you lead. You're energized by multiplying a team's output, not just your own.You're entrepreneurial-minded with an olympian-level work ethic (about half our engineering team are former founders).You own data reliability, quality, and governance as first-class parts of delivery.You care about delivering value to customers, not about what frilly new tech is under the hood.When someone scopes a project for 3 weeks, you ask "why can't it be done in 3 days?" — and you help others develop that same instinct.You're a hacker at heart, with a good sense of which rules should, and shouldn't, be broken.What You'll Be DoingWe 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.Requirements8+ 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.BenefitsCompetitive equity + compensation packageFull family Platinum health insurance, dental, and vision coverage401(k) retirement plan + matchingFlexible work from home or in-officeHealthy lunches are complimentary when working in-office (and breakfast + dinners as needed)Quarterly company off-sites with the teamMacBook provided by usUnlimited PTO (we work hard, but trust you to take time you need to be at your best)Our TechCore business logic in Node.js and TypeScript, with Python in data and ML workflows. AWS across the board (ECS, Lambda, SQS, SNS, Batch, etc.), infrastructure as code with CDK. Data lives in S3, PostgreSQL/Aurora, DynamoDB, Snowflake, and our FHIR server — with Athena for querying S3 and SageMaker for ML. Our data platform is still early: you'll shape what we adopt next, picking the best tool for the job rather than the trendiest one.Metriport provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.