GRAIL - Data Engineer #4885
Requirements
• 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. • 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 • 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.
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.
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