Staff Software Engineer – Data Team #4555
On-siteMenlo Park, California, United States
Job Summary
Design and implement software systems that turn raw clinical, lab, and operational data into reliable, analysis-ready datasets. Develop services, libraries, and workflow components that enforce data integrity, access control, and compliance by design while navigating complex requirements like schema evolution and privacy. Partner with scientists, clinicians, and lab operations to understand data generation needs and lead engineering efforts for long-lived systems evolving alongside active research programs. Mentor engineers and collaborate on cross-functional initiatives involving data quality, testing, and operational excellence. Participate in incident response processes related to data availability issues in production systems.
Required Qualifications
- 7+ years of experience building production-grade software systems
- Strong software engineering fundamentals, including system design, data modeling, API design, and writing well-tested production code
- Experience building and operating data-intensive software systems, not just declarative pipelines or SQL-only workflows
- Proficiency in Go or Python (or similar general-purpose language)
- Experience with data modeling, validation, and transforming real-world data into usable formats
- BS in Computer Science, Engineering or Bioinformatics, or a related field, or equivalent practical experience
Desired Qualifications
- 2+ years experience working in regulated or clinical data environments (e.g., HIPAA, CLIA, GCP, FDA compliance)
- Direct experience working with or supporting scientific teams (e.g., bioinformatics, wet lab, clinical research)
- Experience designing systems that manage laboratory or bioinformatics data (e.g., LIMS, sequencing pipelines, assay metadata)
- Familiarity with GxP practices and regulatory reporting requirements in clinical studies is a plus
- Prior experience working in biotech, diagnostics, or life sciences companies
- Experience supporting sample tracking, structured scientific data pipelines, or cross-functional data lifecycle management
- Experience designing systems with data sequestration, permissioning, or privacy controls
- Experience writing or contributing to software libraries, shared tooling, or reusable components used by other teams
- Advanced degree (MS or PhD) in computer science, engineering, bioinformatics or a related discipline
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