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 & ScopeOwn 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
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
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, mathematics, statistics, bioinformatics, etc.)
Advanced proficiency in Python or R, with strong software engineering fundamentals
Demonstrated experience designing end-to-end data systems and architectures — from ingestion and transformation to orchestration and visualization
Deep understanding of data modeling, pipelines, orchestration, and data quality practices
Proven ability to lead complex, cross-functional projects with significant business or scientific impact
Strong communication skills, with the ability to influence technical and non-technical stakeholders
Experience operating with high autonomy in ambiguous problem spaces
Preferred Qualifications
Experience with distributed systems or system-level programming (Go, Java, C++)
Familiarity with bioinformatics, clinical data systems, or molecular biology concepts
Experience with cloud platforms (AWS) and modern data infrastructure
Experience driving technical strategy, standards, or platform adoption
Intermediate experience with AI-assisted development workflows
Strong SQL and data warehousing expertise
Skills Required
- BS with 8+ years, MS with 5+ years, or PhD with 3+ years of experience in a computational or scientific field
- Advanced proficiency in Python or R
- Experience designing end-to-end data systems and architectures
- Deep understanding of data modeling, pipelines, orchestration, and data quality practices
- Proven ability to lead complex, cross-functional projects
- Strong communication skills to influence stakeholders
- Experience operating with high autonomy in ambiguous problem spaces
- Experience with distributed systems or system-level programming (Go, Java, C++)
- Familiarity with bioinformatics, clinical data systems, or molecular biology concepts
- Experience with cloud platforms (AWS) and modern data infrastructure
- Intermediate experience with AI-assisted development workflows
- Strong SQL and data warehousing expertise
What the Team is Saying
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GRAIL Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as complete across medical, dental, and vision with multiple plan options and added mental‑health and disability support. Additional provisions such as abortion travel benefits reinforce the depth of the healthcare offering.
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Equity Value & Accessibility — Equity is positioned as a meaningful part of total rewards via new‑hire grants, inducement awards, and a discounted ESPP. Compensation materials also highlight equity alongside bonuses and structured market benchmarking.
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Leave & Time Off Breadth — Policies emphasize flexible time off, paid holidays, and company breaks, with a defined parental‑leave program. International entitlements are specifically called out, indicating breadth across regions.
GRAIL Insights
What We Do
GRAIL is a healthcare company whose mission is to detect cancer early, when it can be cured. GRAIL is using the power of high-intensity sequencing, population-scale clinical studies, and state-of-the-art computer science and data science to enhance the scientific understanding of cancer biology, and to develop and commercialize pioneering products.
Why Work With Us
Everything we do is guided by our mission to detect cancer early, when it can be cured. It’s the reason we’re here, and it’s no small task. The right people make all the difference. That’s why we’re looking for those who strive to share their knowledge, contribute their skills, inspire each other and commit to something bigger than themselves.
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GRAIL Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
GRAIL has a variety of work types depending on the roles. Some roles are onsite like a lab role, some are fully remote like our Galleri Sales Consultant roles. Others are hybrid with 2-3 days onsite. Typically Tuesday and Thursday.
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