Staff Software Engineer – Data Team #4555

Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe, and effective technologies that can transform cancer care.

We are a healthcare company, pioneering new technologies to advance early cancer detection. We have built a multi-disciplinary organization of scientists, engineers, and physicians and we are using the power of next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer science and data science to overcome one of medicine’s greatest challenges.

GRAIL is headquartered in the bay area of California, with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies.

For more information, please visit grail.com

Responsibilities

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• Design and implement software systems that turn raw clinical, lab, and operational data into reliable, analysis-ready datasets
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• Partner with scientists, clinicians, lab operations, and data teams to understand data generation, transformation, and usage needs
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• Develop services, libraries, data models, and workflow components that enforce data integrity, access control, and compliance by design
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• Navigate complex data requirements such as schema evolution, blinding, consent, and privacy compliance
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• Collaborate on cross-functional initiatives involving data quality, testing strategy, monitoring, and operational excellence
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• Lead software engineering efforts for long-lived systems that must evolve alongside active clinical and research programs
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• Mentor engineers and collaborate with scientists to ensure software decisions support both technical and scientific outcomes
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• [Contribute to documentation, onboarding materials, and processes that support cross-functional adoption and data literacy across teams]
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• [Participate in incident response or investigation processes related to data quality or availability issues in production systems]
• These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.

Required Qualifications

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• 7+ years of experience building production-grade software systems
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• Strong software engineering fundamentals, including system design, data modeling, API design, and writing well-tested production code.
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• Experience building and operating data-intensive software systems , not just declarative pipelines or SQL-only workflows
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• Proficiency in Go or Python (or similar general-purpose language)
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• Experience with data modeling, validation, and transforming real-world data into usable formats
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• BS in Computer Science, Engineering or Bioinformatics, or a related field, or equivalent practical experience

Preferred Qualifications

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• 2+ years experience working in regulated or clinical data environments (e.g., HIPAA, CLIA, GCP, FDA compliance)
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• Direct experience working with or supporting scientific teams (e.g., bioinformatics, wet lab, clinical research)
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• Experience designing systems that manage laboratory or bioinformatics data (e.g., LIMS, sequencing pipelines, assay metadata)
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• Familiarity with GxP practices and regulatory reporting requirements in clinical studies is a plus
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• Prior experience working in biotech, diagnostics, or life sciences companies
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• Experience supporting sample tracking, structured scientific data pipelines, or cross-functional data lifecycle management
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• Experience designing systems with data sequestration, permissioning, or privacy controls
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• Experience writing or contributing to software libraries, shared tooling, or reusable components used by other teams
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• Advanced degree (MS or PhD) in computer science, engineering, bioinformatics or a related discipline