Job Description
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 GRAIL’s Research department is seeking a Staff Data Engineer to lead the design, development, and evolution of data systems that power GRAIL’s product pipeline, from sample collection through processing, analysis, and regulatory submission. This role operates at the intersection of computational science, engineering, and clinical research, enabling high-impact decision-making across the organization. The Staff Data Engineer is a technical leader who partners with scientists, statisticians, and engineering teams to shape system architecture and deliver robust, analysis-ready datasets. This individual operates with a high degree of autonomy, tackling complex and ambiguous challenges, and influencing cross-functional teams to align on data standards, best practices, and long-term solutions. They will develop deep expertise in GRAIL’s end-to-end data lifecycle, including EDC, LIMS, Bioinformatics Pipelines, and TidyData, an internally-developed system that aggregates and serves combined datasets. They will lead efforts to improve interoperability, scalability, and data quality across these systems. The Staff Data Engineer will also collaborate with software engineers and scientists to develop dataset requirements, develop code and procedures to support dataset generation, perform QC, and troubleshoot issues that arise. As needed, the Staff Data Engineer will also contribute to new reporting, data visualization, and statistical analysis features. Impact & Scope Own and drive large, complex data initiatives that impact multiple teams and stages of the product pipeline Define and evolve data architecture, standards, and best practices across systems Influence technical direction and strategy for data engineering within Research and partner organizations Act as a subject matter expert and technical leader, guiding others and elevating team capabilities Solve ambiguous, high-impact problems requiring deep technical judgment and cross-domain understanding This is a hybrid role based in either Menlo Park, CA (moving to Sunnyvale, CA in Fall 2026) or Durham, NC . 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. Responsibilities Collaborate with data scientists, biostatisticians, and clinical teams to deliver data solutions and sample selections that support clinical trial and research analysis goals Translate complex scientific and analytical requirements into robust, reusable data solutions Contribute to data quality frameworks, including standards for validation, reconciliation, and observability across datasets Drive self-service data platform strategy, implementation and tooling, adoption through training and documentation Lead efforts to standardize and improve dataset generation, QC, and reporting workflows Evaluate and introduce new technologies, methodologies, and best practices to improve data management in a regulated biotechnology environment Mentor other engineers and contribute to technical leadership, standards, and best practices across the organization These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion Required Qualifications BS with 8+ years, MS with 5+ years, or PhD with 3+ years of experience in a computational or scientific field (life science, computer science, engineering, mathemati