Senior Data Analytics Engineer #3968 ID-6787

March 1, 2025

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 Menlo Park, 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.

As a Senior Data Analytics Engineer in Operational Intelligence, you will work collaboratively with stakeholders across GRAIL (Software, Operations, Research, Development, Commercial) to understand the organization-wide needs for data collection, analysis, reporting and application. This position is between Data Engineers, Data Scientists and Data Analysts to curate and transform raw data to produce BI ready datasets. You will build out data marts for new data sources coming into our data warehouse. We are looking for someone who can think strategically but is also hands on with a proven track record building a data ecosystem that delivers compelling business value in a rapidly growing environment. This position is hybrid, working 2 days of the week in office in Durham, NC or in Menlo Park, CA

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Responsibilities:

Design, build, and maintain data models
Collaborate with data analysts, data engineers, and business stakeholders to document data requirements for data marts
Ensure data quality and integrity with testing
Automate and scale common ad-hoc requests
Build out dashboards and reports for different functional teams
Implement code performance on long running queries and conduct code reviews
Lead on our best practices, workflows, and documentation

Preferred Qualifications:

5+ years of directly related experience with a Bachelor’s degree or Master’s degree (preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
5+ years of relevant experience as a data analyst, analytics engineer, or data engineer
3+ years experience with data modeling
2+ years experience with building dashboards and reports in a BI tool
Expert level SQL skills with knowledge of at least one programming language (Python, R, ect.)
Demonstrated positive collaboration skills with key stakeholders and system users to deliver robust systems and compelling results
Experience with AWS (Redshift, S3, Glue, Managed Airflow) Snowflake, Tableau
Experience with SaaS application data sets (Netsuite, Salesforce, Workday, Coupa)
Life sciences / BioTech sector experience in a regulated environment

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