As a Data Engineer on the Operational Technology team, you will build and maintain the data pipelines that connect GRAIL's lab instruments, automation systems, and operational platforms to a trusted, well modeled data foundation. You will own well scoped ingestion and transformation pipelines end to end, partnering with systems engineers, lab operations, data scientists, and automation engineers to keep data flowing reliably from the lab floor to the analytics and AI systems that depend on it. This is a hands-on role for an engineer who is ready to take ownership of real data infrastructure and grow quickly in a fast paced, regulated environment. Expect to work alongside a talented and highly motivated team that moves quickly.
This role is based on-site in RTP, North Carolina, Monday through Friday. The position participates in an on-call rotation and may occasionally require weekend or holiday support for production incidents, maintenance, or critical deployments.
Responsibilities:
Build and maintain data pipelines that ingest and integrate information from laboratory instruments, automation systems, sequencers, operational platforms, APIs, autonomous robotics platforms, databases and file based data sources.
Support downstream analytics, reporting, and AI systems by delivering clean, trustworthy datasets and timely data extracts for troubleshooting, root-cause investigations and platform improvements.
Develop and optimize SQL and transformation logic to cleanse, standardize, and model raw instrument and production data into reliable, well structured datasets.
Build and support datasets and data models used by operational dashboards, analytics, process monitoring, troubleshooting, and governed AI enabled workflows.
Implement orchestration, testing, monitoring and alerting so that data failures, freshness issues, schema changes, and incomplete processing are identified early.
Implement data validation and quality checks to ensure datasets are accurate, complete, and reliable.
Document pipelines, data models, and datasets to support reproducibility and compliance with ISO, CLIA, CAP, NYS, GMP, and FDA requirements.
Continuously improve your technical skills and the team's engineering practices.
Required Qualifications:
Degree in Computer Science, Mathematics, Software Engineering, Data Science, Life Sciences, Physics or similar field.
1+ years of relevant professional, internship, academic, or project experience in data engineering, analytics engineering, software development, or a related field, or equivalent practical experience.
Proficiency in SQL.
Working proficiency with one or more programming languages, such as Python, Rust, C++, or similar.
Basic understanding of ETL or ELT pipelines, relational databases, and structured or semi-structured data.
Strong attention to detail and a commitment to data quality, reliability and accuracy.
Ability to collaborate effectively in teams of technical and non-technical individuals, and comfortable working in a rapidly changing environment with dynamic objectives and fast iteration.
Ability to investigate technical problems methodically, continuously learn and communicate clearly.
A highly analytical mindset and eagerness to solve technical problems.
Preferred Qualifications:
Familiarity with data pipeline orchestration and transformation tools such as Airflow, dbt, or comparable technologies.
Familiarity with cloud data platforms, object storage and warehouses such as AWS S3, Redshift, Glue, Snowflake or comparable technologies.
Familiarity integrating AI/agentic tooling into the data engineering SDLC.
Experience with semantic data modeling, data lineage, and automated data quality testing.
Familiarity with statistical methods or basic process analytics.
Exposure to manufacturing, clinical laboratory operations, diagnostics, or biotechnology.
Experience with version control systems such as Git and collaborative development practices.
Basic understanding of APIs, file transfers, networking and system integrations.
The expected, full-time, annual base pay scale for this position is $86K - $106K. Actual base pay will consider skills, experience, and location.
This role may be eligible for other forms of compensation, including an annual bonus and/or incentives, subject to the terms of the applicable plans and Company discretion. This range reflects a good-faith estimate of the range that the Company reasonably expects to pay for the position upon hire; the actual compensation offered may vary depending on factors such as the candidate’s qualifications. Employees in this role are also eligible for GRAIL’s comprehensive and competitive benefits package, offered in accordance with our applicable plans and policies. This package currently includes flexible time-off or vacation; a 401(k) retirement plan with employer match; medical, dental, and vision coverage; and carefully selected mindfulness programs.
GRAIL is an equal employment opportunity employer, and we are committed to building a workplace where every individual can thrive, contribute, and grow. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, age, disability, status as a protected veteran, , or any other class or characteristic protected by applicable federal, state, and local laws. Additionally, GRAIL will consider for employment qualified applicants with arrest and conviction records in a manner consistent with applicable law and provide reasonable accommodations to qualified individuals with disabilities. Please contact us at [email protected] if you require an accommodation to apply for an open position.
GRAIL maintains a drug-free workplace. We welcome job-seekers from all backgrounds to join us!
Skills Required
- Degree in Computer Science, Mathematics, Software Engineering, Data Science, Life Sciences, Physics, or a similar field
- At least 1 year of relevant professional, internship, academic, or project experience in data engineering, analytics engineering, software development, or a related field, or equivalent practical experience
- Proficiency in SQL
- Working proficiency in one or more programming languages, such as Python, Rust, C++, or similar
- Basic understanding of ETL or ELT pipelines, relational databases, and structured or semi-structured data
- Strong attention to detail and commitment to data quality, reliability, and accuracy
- Ability to collaborate with technical and non-technical teams in a rapidly changing environment
- Ability to investigate technical problems methodically, learn continuously, and communicate clearly
- Analytical mindset and eagerness to solve technical problems
- Familiarity with data pipeline orchestration and transformation tools such as Airflow or dbt
- Familiarity with cloud data platforms, object storage, and warehouses such as AWS S3, Redshift, Glue, or Snowflake
- Familiarity integrating AI or agentic tooling into the data engineering software development lifecycle
- Experience with semantic data modeling, data lineage, and automated data quality testing
- Familiarity with statistical methods or basic process analytics
- Exposure to manufacturing, clinical laboratory operations, diagnostics, or biotechnology
- Experience with version control systems such as Git and collaborative development practices
- Basic understanding of APIs, file transfers, networking, and system integrations
What the Team is Saying
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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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