Lead Data Platform Architect

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.

• 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).

• 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)

• 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 Data Factory

Data governance, access control, and sensitive/anonymised data handling

Hands‑on experience with CDISC standards (SDTM, ADaM)

Microsoft Fabric

Preferred skills

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