About The Position

Design, build, and govern cloud-based data platforms that turn heterogeneous, multi-country life-sciences data into trusted, reusable data products. The role spans clinical trial data, real-world data (RWD), and omics — harmonising these into standardised, regulatory-grade, analysis-ready assets. Combines hands-on engineering on Azure and Databricks with technical leadership of a multidisciplinary team.

Requirements

  • 8+ years in data engineering, with substantial Life Sciences / pharmaceutical experience.
  • Proven delivery of cloud data platforms on Azure and Databricks; familiarity with Microsoft Fabric.
  • Strong proficiency in Python and SQL, plus ETL/ELT orchestration (Azure Data Factory).
  • Hands-on experience with CDISC standards (SDTM, ADaM) and clinical data workflows.
  • Relational and non-relational stores: SQL Server, PostgreSQL, MongoDB.
  • Data governance, access control, and sensitive/anonymised data handling.
  • Team leadership and Agile delivery (Scrum, SAFe, Kanban).

Nice To Haves

  • OMOP CDM and real-world data standardisation experience.
  • Omics / bioinformatics data and large-scale scientific datasets.
  • Graph databases (Neo4j) and knowledge-graph modelling.
  • BI & visualisation: Power BI, Metabase, Streamlit.
  • Databricks Certified Data Engineer (Associate / Professional)
  • Microsoft Certified: Azure Data Engineer / Fabric Analytics Engineer Associate
  • Neo4j Certified Professional
  • Professional Scrum Master (PSM I / II)
  • Cross-functional collaboration with scientific and business stakeholders.
  • Clear communication of technical concepts to non-technical audiences.
  • Multilingual capability for global study support (an asset).
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