Responsibilities
- Contribute to a highly collaborative team focused on delivering value to cross-functional partners by implementing processes and tools that prepare analysis-ready datasets.
- Integrate inputs from diverse data sources across the organization into well-structured, harmonized datasets.
- Build and maintain access controls and data-delivery mechanisms that uphold stringent blinding and privacy standards.
- Partner with Research, Clinical Lab Operations, and Software Engineering teams to define and implement data transformations that support downstream analysis.
- Ensure all delivered data adheres to software quality expectations, clinical compliance requirements, sequestration protocols, and privacy regulations.
- Implement automated testing and release processes to improve the reliability, quality, and velocity of software and data deliveries.
- Mentor engineers and scientists, promoting best practices in software development, data engineering, and operational rigor.
Preferred Qualifications
- BS/MS/PhD in a quantitative field (e.g., Computer Science, Engineering, Mathematics, Statistics, Bioinformatics) or equivalent and 6+ years of experience in data engineering, ideally within a regulated biotechnology, pharmaceutical, medical device, or healthcare environment.
- Deep knowledge of ETL/ELT workflows, data pipeline development, and database management, with demonstrated success delivering data solutions for clinical or regulatory use cases.
- Expertise in SQL and proficiency in Go and Python. Experience with R would be nice to have.
- Experience with cloud-based data platforms (AWS, Azure, or Google Cloud) and preferably an understanding of compliance frameworks such as HIPAA and GDPR.
- Strong analytical and problem-solving skills, with a track record of maintaining data quality and integrity across complex datasets.
- Proven experience working on cross-functional teams and translating user requirements into scalable, high-quality data solutions.
- Hands-on experience with relational databases, data modeling, data pipeline tools, and workflow engines (e.g., SQL, dbt, Apache Airflow, AWS Glue, Spark).
- Familiarity with DevOps practices, including CI/CD pipelines, containerized deployment (e.g., Kubernetes), and infrastructure-as-code (e.g., Terraform).
- Ability to navigate ambiguity, refine evolving requirements, and work with product and stakeholder teams to drive clear engineering objectives and designs.
- Excellent written and verbal communication skills, with the ability to tailor technical content to diverse audiences.
Top Skills
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.
Gallery
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 are onsite like a lab role, others are hybrid and still others are remote. Hybrid is typically Tuesday and Thursday but leaders may be flexible depending on the role.












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