Staff Software Engineer – Data Team #4555

Responsibilities

• Design and implement software systems that turn raw clinical, lab, and operational data into reliable, analysis-ready datasets
• Partner with scientists, clinicians, lab operations, and data teams to understand data generation, transformation, and usage needs
• Develop services, libraries, data models, and workflow components that enforce data integrity, access control, and compliance by design
• Navigate complex data requirements such as schema evolution, blinding, consent, and privacy compliance
• Collaborate on cross-functional initiatives involving data quality, testing strategy, monitoring, and operational excellence
• Mentor engineers and collaborate with scientists to ensure software decisions support both technical and scientific outcomes
• Contribute to documentation, onboarding materials, and processes that support cross-functional adoption and data literacy across teams
• Participate in incident response or investigation processes related to data quality or availability issues in production systems

Requirements

• 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

Qualifications

• BS in Computer Science, Engineering or Bioinformatics, or a related field, or equivalent practical experience
• 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