Senior Data Engineer – Biopharma

About the role

Help a biopharma scale secure, high‑quality data pipelines that power manufacturing analytics and AI use cases (yield, deviation prediction, batch release). You’ll own ingestion and transformation from OT/IT systems into a governed lakehouse, ensuring GxP-compliant design and documentation.

What you’ll do

• Build and optimize batch/streaming pipelines (ETL/ELT) across MES/LIMS/ERP/Historians into a lake/lakehouse (e.g., Delta/Snowflake).
• Engineer reusable frameworks for data quality, lineage, and observability aligned to ALCOA+ and data integrity.
• Partner with Manufacturing, QA, and Data Science to productionize features for ML and BI.
• Implement role-based access, PII handling, and audit trails aligned to GxP/Annex 11.
• Contribute to validation packages (requirements, risk, test, traceability).

Your background

• 5–8+ years in data engineering; pharma/biotech or other regulated industry experience.
• Strong in Databricks/Spark (or PySpark), Azure/AWS/GCP , SQL, and orchestration (ADF, Airflow, Prefect).
• Hands‑on with Delta Lake/Snowflake and med‑device/pharma data sources: MES (e.g., PAS‑X) , LIMS, OSIsoft PI/AVEVA, SAP S/4HANA .
• Working knowledge of GxP, GMP, CSV/CSA, Annex 11 , and documentation in regulated environments.
• Familiarity with data governance (catalog/lineage), e.g., Purview/Collibra .

Nice to have

• CDC tools (Fivetran/DBT), Kafka/Event Hubs, Infra-as-code (Terraform).
• Exposure to feature stores , MLflow, or MLOps pipelines.

What’s on offer

• Competitive day rate; remote‑first within Europe
• Engagement via compliant models (e.g., B2B/SRL/BV, umbrella, or EOR) subject to country guidance
• Work that directly accelerates safe medicines to patients