Senior Data Engineer

BioTalent; San Diego (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

BioTalent in San Diego, CA, is seeking a Senior Data Engineer to own end-to-end data architecture for a wearable medical device startup. You will translate clinical, regulatory and commercial needs into instrumentation specs and build infrastructure, schemas, and systems from scratch.

You'll work with telemetry, clinical outcomes, EDC data, and manufacturing data, and ensure lineage and auditability for regulatory submissions, while collaborating with cross-functional teams.

Qualifications

• 7+ years of data engineering experience in production data systems.
• Experience defining data models and instrumentation upstream of pipelines.
• Familiarity with CDISC SDTM/ADaM and regulated data environments.

Responsibilities

• Define data to collect from device, manufacturing and business operations.
• Design and own data schemas serving analytical, regulatory and operational users.
• Build and maintain ETL/ELT pipelines on Google Cloud and BigQuery.
• Own warehouse layer: schema, access controls and data quality monitoring.
• Maintain traceable lineage and transformation logic for regulatory audits.
• Integrate with EDC systems and third-party device data.
• Produce CDISC-compliant datasets (SDTM/ADaM) for submissions.
• Build manufacturing data infrastructure: lot tracking and supply chain data.
• Define data quality metrics and lead fixes; assist analysis as needed.

Skills

Data architecture

Data pipelines

Python

SQL

Data modeling

CDISC knowledge

Regulatory data audits

Communication with stakeholders

Education

MS in computer science or related field

Tools

Google Cloud

BigQuery

Firestore

Castor

REDCap

Medidata Rave

Veeva Vault

Job description

Senior Data Engineer | Medical Device Startup | San Diego, CA (Hybrid, 3+ days onsite)

A venture-backed startup developing a novel wearable medical device is hiring a Senior Data Engineer. The company is running multiple clinical trials leading toward a pivotal FDA submission.

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 BigQuery
• 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 it

WHAT YOU BRING

• 7+ 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, BigQuery 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 stakeholders
• Experience 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 health
• MS 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.