Senior Data Engineer

THE ROLE: This role owns the company's data architecture end to end and reports to the Director of Data Science. The work starts upstream: you'll make sure the right data is collected in the first place by turning clinical, regulatory and commercial needs into instrumentation specs, then build the infrastructure that makes that data useful. It's hands-on. You'll design schemas and implement them, contribute to product concepts, and build several systems from scratch. The data includes telemetry from embedded and mobile systems with intermittent connectivity, clinical outcomes, EDC data, and evolving manufacturing and production systems.

WHAT YOU'LL DO: Define what data to collect from the device, manufacturing and business operations, and translate those needs into instrumentation specs and data models Design and own data schemas that serve analytical, regulatory and operational users, and document the tradeoffs Build and maintain transformation pipelines on Google Cloud and Big Query Own the warehouse layer, including schema implementation, versioning, access controls and data quality monitoring Keep lineage and transformation logic traceable to a standard that holds up in a regulatory audit Build integrations with EDC systems and third-party device data Produce CDISC-compliant datasets (SDTM/ADaM) for regulatory submissions Build manufacturing data infrastructure: lot tracking, supply chain, process control and non-destructive testing records Define data quality metrics and checks, own the fixes, and step into analysis when the team needs itWHAT YOU BRING7+ years of data engineering experience, with a track record of owning production data systems end to end Experience defining data models and instrumentation requirements upstream of pipeline development Strong Python and SQL, plus working knowledge of cloud data platforms (the stack is Google Cloud, Big Query and Firestore)Strong data modeling skills, with the judgment to serve multiple users and make tradeoffs explicit Experience turning business and scientific requirements into specs across data science, engineering, operations, clinical and regulatory teams Clear, direct communication with non-technical stakeholdersNICE TO HAVEExperience in a regulated industry (medical devices, pharma or clinical research) where auditability and traceability are required Familiarity with CDISC (SDTM/ADaM) or clinical trial data formats Experience with EDC systems such as Castor, REDCap, Medidata Rave or Veeva Vault Exposure to 21 CFR Part 11 Experience with manufacturing, supply chain or operational data systems Background in medical devices, wearables or digital healthMS in computer science, data engineering, biomedical informatics or a related field Candidates must be authorized to work in the U.S. without sponsorship and must live within commuting distance of San Diego.