Senior Data Analytics Engineer # 4527

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