For an international organisation operating in a highly regulated life sciences environment, we are looking for a Lead Data Platform Architect.

You will play a key role in designing, building and governing modern cloud-based data platforms that transform complex, multi-country scientific and healthcare data into trusted, reusable and analysis-ready data products.

The environment combines clinical trial data, real-world data (RWD) and omics data within a modern Azure ecosystem. The focus is on building scalable, compliant and future-proof data platforms that support research, regulatory processes and data-driven decision-making.

This role combines hands-on architecture and engineering responsibilities with technical leadership across multidisciplinary teams.

Responsibilities

Clinical Data Harmonisation

• Design and maintain data pipelines that consolidate clinical data from multiple studies, vendors, EDC systems and countries into a unified and governed data model.
• Implement and maintain CDISC standards, including SDTM and ADaM, to ensure consistency and regulatory readiness.
• Define mapping specifications, controlled terminologies and harmonisation frameworks across clinical datasets.
• Establish data quality, lineage and reconciliation processes to resolve structural and semantic inconsistencies.
• Govern access to sensitive, anonymised and key-coded datasets according to defined data access policies.

Real-World Data Standardisation

• Integrate and standardise healthcare data sources including claims data, electronic health records (EHR), registries, wearables and patient-reported outcomes.
• Build scalable ETL/ELT processes that normalise and harmonise healthcare vocabularies such as SNOMED, ICD, LOINC and RxNorm.
• Implement quality, completeness and conformance controls to support epidemiology, HEOR and regulatory evidence generation.
• Ensure consistency across providers, countries and coding systems.

Omics Data Management

• Design scalable storage and processing solutions for large-scale genomics, transcriptomics and proteomics datasets.
• Develop data pipelines that connect molecular, clinical and phenotypic data.
• Support biomarker discovery and translational research initiatives.
• Apply FAIR principles and metadata standards to ensure discoverability, interoperability and reproducibility of scientific assets.

Platform Engineering & Architecture

• Architect and maintain a modern Lakehouse platform based on Azure Databricks and Microsoft Fabric.
• Design and optimise Medallion architectures (Bronze, Silver and Gold layers).
• Develop production-grade solutions using:
  • Azure Data Factory
  • Databricks
  • Apache Spark
  • Python
  • SQL
• Implement automated governance frameworks and policy enforcement mechanisms.
• Manage CI/CD, version control and Infrastructure as Code using Git, GitHub and Azure DevOps.
• Ensure platform scalability, reliability and maintainability.

Governance, Compliance & Leadership

• Ensure compliance with industry regulations and data integrity standards, including:
  • GxP
  • GDPR
  • 21 CFR Part 11
  • ALCOA+
• Lead and mentor a team of data engineers and analysts.
• Define technical standards and engineering best practices.
• Drive continuous improvement and engineering excellence.
• Collaborate closely with stakeholders across scientific, technical and business domains.
• Translate research and business requirements into governed and scalable data products.

Requirements

Mandatory Experience

• Minimum 8 years of experience in Data Engineering, Data Platform Engineering or Data Architecture.
• Strong background within Life Sciences, Clinical Research, Biotechnology or Pharmaceutical environments.
• Proven experience designing and delivering enterprise-scale cloud data platforms on Azure and Databricks.
• Hands-on experience with Microsoft Fabric.
• Strong expertise in:
  • Python
  • SQL
  • Azure Data Factory
• Demonstrated experience with:
  • CDISC
  • SDTM
  • ADaM
  • Clinical data workflows
• Experience with:
  • SQL Server
  • PostgreSQL
  • MongoDB
• Strong understanding of:
  • Data Governance
  • Data Lineage
  • Access Management
  • Sensitive and anonymised data handling
• Experience leading engineering teams.
• Experience working in Agile delivery environments (Scrum, SAFe or Kanban).

Preferred Experience

• OMOP Common Data Model (OMOP CDM)
• Real-World Data (RWD) standardisation
• Epidemiology and HEOR environments
• Omics and Bioinformatics platforms
• Large-scale scientific datasets
• Neo4j and Knowledge Graph modelling
• Power BI
• Metabase
• Streamlit

Preferred Certifications

• Databricks Certified Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Fabric Analytics Engineer Associate
• Neo4j Certified Professional
• Professional Scrum Master (PSM)

Personal Skills

• Strong stakeholder management and communication skills.
• Ability to bridge technical and scientific domains.
• Comfortable operating in international and multidisciplinary environments.
• Able to explain complex technical concepts to non-technical stakeholders.
• Proactive, pragmatic and solution-oriented mindset.

Assignment Highlights

• Strategic data platform programme within a highly regulated scientific environment.
• Combination of architecture, hands-on engineering and technical leadership.
• Modern Azure ecosystem including Databricks, Fabric and Data Factory.
• High-impact role supporting clinical, real-world and omics data domains.
• Fully remote engagement within Northwest Europe.
• Long-term assignment with potential for extension.