Data Engineer # 4885

Responsibilities:

• Build evolve and support dashboards reports and real-time monitoring tools for functional teams and executives that clearly communicate findings and drive data-informed decisions.; enable self-serve analytics and automate common ad hoc requests.

• Implement and continuously improve process monitoring systems (e.g. SPC automated controls alerting) to track and stabilize process health.

• Define govern and report KPIs for throughput quality efficiency and compliance; proactively surface trends anomalies and risks.

• Develop and deploy predictive analytics trend analyses and models to anticipate process equipment and quality issues; partner with Data Science on model integration and deployment.

• Collect cleanse and analyze process and production data from high-throughput lab environments; ensure timely reliable access to accurate datasets.

• Provide rapid data extracts and tailored analyses to expedite troubleshooting containment and root-cause investigations.

• Ensure data quality and integrity through robust testing validation lineage and observability; establish and monitor SLAs for critical datasets.

• Maintain comprehensive process documentation compliant with ISO CLIA CAP NYS GMP and FDA requirements; ensure monitoring and reporting systems are audit-ready.

• These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.

Required Qualifications:

• Bachelor’s degree in Computer Science Statistics Informatics Information Systems Engineering Data Science Life Sciences or a related quantitative field.

• 5+ years of relevant experience as a data analyst analytics engineer or data engineer delivering production-grade datasets dashboards and reports.

• 3+ years of data modeling experience (dimensional/semantic).

• 2+ years building dashboards and reports in a modern BI platform (e.g. Tableau).

• Proficiency in SQL and at least one programming language (Python or R).

• Hands-on experience with AWS analytics services (e.g. Redshift S3 Glue Managed Airflow) and/or Snowflake.

• Experience working with SaaS application data sources (e.g. NetSuite Salesforce Workday Coupa).

• Proven expertise in process analytics SPC statistical methods and root-cause analysis (e.g. JMP Minitab; SQL; Python/R).

• Demonstrated ability to collaborate with stakeholders and system users to deliver robust solutions and measurable results.

• Experience in regulated life sciences/biotech environments and familiarity with clinical laboratory operations.

Preferred Qualifications:

• 5+ years of laboratory operations experience in regulated medical device diagnostics or biotechnology settings.

• Master’s preferred.

• Experience deploying and scaling process monitoring in high-throughput or automated environments.

• Knowledge of end-to-end clinical lab workflows (sample shipment; pre-analytical analytical and post-analytical phases).

• Strong understanding of regulatory and QMS frameworks (GMP ISO 13485 ISO 15189 CLIA CAP NYS FDA).

• Excellent leadership communication and cross-functional collaboration 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.

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