Lead Data Platform Architect

We are looking for a Lead Data Platform Architect for our client in the Pharma Industry 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. Clinical Data Harmonisation Design and operate pipelines that consolidate clinical data across studies, vendors, EDC systems, and countries into a single harmonised model. Implement and enforce CDISC standards (SDTM, ADaM), controlled terminologies, and mapping specifications for cross-study consistency and submission readiness. Build reconciliation, lineage, and data-quality frameworks that resolve structural and semantic differences between source datasets. Manage classification and access of sensitive datasets, including key-coded and anonymised Individual Human Data (IHD), under domain-driven access policies. Real-World Data Standardisation Integrate and standardise RWD sources — claims, EHR, registries, wearables, patient-reported outcomes — into a common data model (e.g., OMOP CDM). Automate ETL/ELT workflows that normalise vocabularies (SNOMED, ICD, LOINC, RxNorm) and reconcile coding systems across providers and geographies. Establish quality, completeness, and conformance checks that make RWD fit for epidemiology, HEOR, and regulatory evidence generation. Omics Data Management Build scalable storage and processing patterns for high-volume, high-dimensionality omics data (genomics, transcriptomics, proteomics). Engineer pipelines that link molecular data with clinical and phenotypic data to support translational and biomarker research. Apply metadata, FAIR principles, and reference standards so omics assets are discoverable, interoperable, and reproducible. Platform Engineering & Architecture Architect and maintain a lakehouse / Medallion (Bronze–Silver–Gold) platform on Azure Databricks and Microsoft Fabric. Develop production-grade pipelines using Azure Data Factory, Spark, SQL, and Python. Implement automated data governance and policy enforcement (e.g., Open Policy Agent / OPA) applying business and access rules by domain. Manage CI/CD, version control, and infrastructure-as-code via Git/GitHub and Azure DevOps. Governance, Compliance & Leadership Ensure platforms meet pharma regulatory and data-integrity expectations (GxP, GDPR, 21 CFR Part 11, ALCOA+). Lead, mentor, and grow a team of data engineers and analysts; foster engineering excellence and continuous improvement. Partner with biostatistics, clinical data management, bioinformatics, and business stakeholders to translate scientific needs into governed data products. What Success Looks Like Harmonised, standards-compliant data products available across clinical, RWD, and omics domains. Reduced data-retrieval time and improved accessibility of governed, high-quality datasets. A high-performing engineering team delivering reliable platforms that withstand regulatory scrutiny. Required Skills 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). Start date: ASAP End date: 28-06-2027 Location: Onshore Northwest Europe (excl. Nordics) For the duration of this assignment Ework Services (0,9%) will be deducted from the total amount invoiced. We offer candidates continuously. This means that we sometimes remove the assignments before deadline. If you are interested, we recommend that you apply immidiately.