Lead Data Platform Architect 12 Months Contract

Role Summary

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

Required (Must-Have)

• 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).

Preferred (Nice-to-Have)

• 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.
• Certifications (Preferred) Databricks Certified Data Engineer (Associate / Professional) Microsoft Certified: Azure Data Engineer / Fabric Analytics Engineer Associate Neo4j Certified Professional Professional Scrum Master (PSM I / II)

Soft Skills

• 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).
• Team leadership and Agile delivery (Scrum, SAFe, Kanban)
• Strong proficiency in Python and SQL
• clinical data workflows
• Pharmaceutical experience
• ETL/ELT orchestration
• SQL Server, PostgreSQL, MongoDB
• Proven delivery of cloud data platforms on Azure and Databricks
• 8+ years in data engineering
• Azure DataFactory
• Data governance, access control, and sensitive/anonymised data handling
• Hands-on experience with CDISC standards (SDTM, ADaM)
• Microsoft Fabric
• OMOP CDM and real-world data standardisation experience
• Omics / bioinformatics data and large-scale scientific datasets
• BI & visualisation: Power BI, Metabase, Streamlit
• Graph databases (Neo4j) and knowledge-graph modelling