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.

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GRAIL is seeking a Staff Software Engineer for the Data Team. This team designs, builds, and operates the software systems that manage GRAIL’s end-to-end data lifecycle, from sample ingestion through downstream analysis, while meeting rigorous clinical, regulatory, and privacy standards. Our work directly supports clinical research, operations, and decision-making in the fight against cancer.

In this role, you will take technical ownership of systems that produce trusted, analysis-ready datasets for use across GRAIL’s research and clinical programs. This is a software engineering role focused on building complex production-grade systems that work with data in dynamic, regulated environments as opposed to assembling off-the-shelf ETL tools or writing SQL heavy pipelines. This position offers significant autonomy and scope for impact.

You’ll collaborate closely with research, clinical lab operations, and scientific teams
, and lead efforts to improve how we structure, validate, and deliver critical scientific and clinical data.

This role is based in Menlo Park, California, and will move to Sunnyvale, California in Fall 2026. It offers a flexible work arrangement, with the ability to work from GRAIL's office or from home. Our current flexible work arrangement policy requires that a minimum of 60%, or 24 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 60% requirement for the site.

At our Menlo Park campus, Tuesdays and Thursdays are the key days where we encourage on-site presence to engage in events and on-site activities.

• 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
• Lead software engineering efforts for long-lived systems that must evolve alongside active clinical and research programs
• 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

These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.

• 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…