Bridge Data Engineering, Data Science, and Analytics to curate and transform raw operational and laboratory data into BI-ready datasets and scalable data products.
Collaborate across Software, Operations, Research, Development, and Commercial to design and sustain a robust data ecosystem.
Perform analysis and build and maintain dashboards and analytical tools that monitor high-throughput lab processes.
Ensure the accuracy, accessibility, and utility of data and reporting systems that are critical to lab efficiency, traceability, and product quality.
Deliver trusted insights that drive measurable business value in a rapidly growing environment.

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.

Senior Data Analytics Engineer

Key skills