{"id":29025,"url":"https://alion.io/job/metriport-senior-data-engineer","title":"Senior Data Engineer","company":{"id":849,"name":"Metriport","domain":"metriport.com","url":"https://alion.io/company/metriport","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"BigQuery","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-07-30T18:20:42Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-16T23:13:35Z","board_verified":true,"closed_at":null,"days_open":78,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":78},"description":"About Us\nMedical data exchange is one of the biggest unsolved problems in US healthcare. If you've spent any real time in the healthcare system, you've felt it, and it only gets worse the sicker and older you get. Metriport exists to fix that. We connect to the data sources the healthcare providers of tomorrow need, take raw data that's unusable in its source form, and turn it into a single clean format that care teams, and their agents, actually use to improve outcomes. Record retrieval across thousands of legacy systems and antiquated data pipes that used to take weeks now takes seconds. Clinicians walk into appointments with the full patient picture already in hand, and that speed can mean spotting a condition early enough to actually treat it.\nWe're not a healthcare company. We're a technology company that happens to operate in healthcare, and we build every layer ourselves: connect, transform, and insight. Legacy EHRs were built to get providers paid, not to serve the clinical experience. We're building what should have existed instead: the system of record for all of US healthcare. We started in data exchange. Today we compete with the largest data platforms in the space. Tomorrow we will be the infrastructure layer healthcare runs on.\nWe’ve raised $28.4 million from top-tier VCs (including Matrix, ARTIS and Y Combinator), found product-market fit (multi-million dollar ARR, 100+ customers including Amazon One Medical, Circle Medical, Color Health, and Strive Health), and have years of runway ahead of us. If you’ve had a good healthcare experience in the past few years, there’s a good chance Metriport was behind it. That’s the version of healthcare we want people to not just expect, but demand. Join us and build the future.\nAbout You\nWe're a small, high-output team, mostly former founders including YC alumni, and we operate with real autonomy and almost no bureaucracy. We hire on competence, not pedigree. Leaders are in the office six days a week, and we generally expect the team to be available six days a week too. Not because we count hours, but because there's always more wood to chop when revolutionizing how tomorrow’s healthcare providers deliver care to their patients today. We trust our team to take the time off they need and we've never said no to a time off request.\nYou have an entrepreneurial mindset and a strong sense of ownership. You don't wait to be told what's broken. Instead, you believe you can figure out any problem that lands in your lap even outside your exact domain. When someone scopes something for three weeks, you ask why it can't be done in three days, and you also know the difference between shipping a fast v0 and cutting a corner that comes back to bite you. You walk the tightrope between craft and speed without falling off either side.\nThe role\nWe're looking for a data engineer who can operate at a Senior level:\nYou've built and scaled data pipelines and systems, with hands-on experience across the ecosystem - distributed processing, lakehouses, warehouses, streaming, orchestration. You know when each is (and isn't) the right tool for the job, and people usually come to you for guidance on how to move, transform, and serve data reliably.\n\nYou fully own your work - technical decisions, delivery, results - and you level up the engineers around you through code reviews, pairing, and guidance. Multiplying the team's output energizes you as much as shipping your own.\n\nYou're entrepreneurial-minded with an olympian-level work ethic (about half our engineering team are former founders).\n\nYou understand data reliability, quality, and governance as first-class parts of delivery.\n\nYou care about delivering value to customers, not about what frilly new tech is under the hood.\n\nWhen 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.\n\nYou're a hacker at heart, with a good sense of which rules should, and shouldn't, be broken.\n\nWhat you'll be doing\nWe ingest clinical data for millions of patients from external healthcare sources, with continuous updates for a growing subset of those patients. You'll be a catalyst to scale the data platform that powers our product - and ship it to customers fast.\nDay to day, that looks like:\nRaising 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).\n\nDriving data projects end-to-end: writing Design Documents, shipping v0's quickly, and iterating to v1 and beyond.\n\nSupporting AI/ML efforts - making sure the AI Engineers have the data they need.\n\nMultiplying the team: mentoring engineers on data fundamentals, reviewing designs and PRs, and judging when to invest in quality vs. ship fast.\n\nParticipating 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.\n\nExample projects you could own:\nScaling our patient data consolidation pipeline (deduplication, normalization, hydration) to handle 100x today's volume without 100x the cost.\n\nBuilding pipelines that deliver clinical data directly into customers' data warehouses, reliably and at scale.\n\nBuilding the ingestion path for customers pushing large volumes of their own data into the platform.\n\nBuilding document-processing pipelines that extract structured data from PDFs, images, and free text to feed ML models.\n\nRequirements\n6+ 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.\n\nExperience across the data stack - ingestion, storage, processing, warehousing, serving - and an understanding of the tradeoffs (cost, latency, correctness, operability) at each layer.\n\nExperience with modern, cloud-native data stacks: e.g., Spark, open table formats (Parquet, Iceberg, Delta) on S3, and warehouses (Snowflake, BigQuery, Redshift).\n\nStrong software engineering fundamentals - you write production code (we're a TypeScript shop, with Python in data/ML workflows), not just orchestration configs.\n\nExperience mentoring or guiding other engineers - through code reviews, pairing, design feedback, or onboarding.\n\nLocated in San Francisco / Bay Area, or willing to relocate.\n\nBonus:\nExperience with streaming systems (Kafka, Kinesis), dbt, or orchestration tooling (Airflow, Dagster).\n\nExperience building or supporting ML/data science workflows (feature pipelines, model inputs/outputs, unstructured data extraction).\n\nHealthcare standards/technologies: FHIR, HIE, IHE, EHR/EMR, NPI, TEFCA, ADT, HL7, HEDIS, RAF, SNOMED, LOINC, ICD-10, etc.\n\nBenefits\nCompetitive equity + compensation package\n\nFull family Platinum health insurance, dental, and vision coverage\n\n401(k) retirement plan + matching\n\nFlexible work from home or in-office\n\nHealthy lunches are complimentary when working in-office (and breakfast + dinners as needed)\n\nMacBook provided by us\n\nUnlimited PTO (we work hard, but trust you to take time you need to be at your best)\n\nOur tech\nCore 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.\nMetriport 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. 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