Forward Deployment Engineer/Azure Data Engineer

We are looking for an experienced Senior Azure Data Engineer/Forward Deployed Data Engineer to lead the design and delivery of enterprise-scale data solutions within a complex Life Sciences environment. This is a highly hands-on role combining deep Azure Data Engineering expertise with strong client-facing delivery. You will take end-to-end ownership of POD deliverables, working directly with technical and business stakeholders to rapidly gather feedback, resolve issues and deploy production-ready solutions., * Design, build and optimise enterprise-scale data pipelines using PySpark, Python, SQL and Databricks.

• Architect and deliver Azure data solutions using Azure Data Factory (ADF), ADLS Gen2, Synapse and Event Hubs.
• Design and implement Data Warehouse, Data Lake and Lakehouse architectures.
• Take full accountability as the single point of ownership for end-to-end POD deliverables.
• Work directly with stakeholders to understand requirements, manage ambiguity and translate business problems into technical solutions.
• Gather Real Time user and stakeholder feedback, troubleshoot edge cases and deploy improvements rapidly.
• Work across cross-functional PODs and global delivery teams to drive solutions from initial requirement through to production.
• Implement engineering best practices across Git, Azure DevOps, CI/CD, automated testing and data governance.
• Support integration of GenAI frameworks into data engineering and automated RCA/data augmentation workflows.
• Communicate complex technical solutions clearly to both technical and non-technical stakeholders.

• 10+ years’ Data Engineering experience, including building enterprise-scale data pipelines.
• Strong hands-on experience with PySpark, SQL, Python and Databricks.
• Deep expertise across the Microsoft Azure data ecosystem, particularly:
• Azure Data Factory (ADF)
• ADLS Gen2
• Azure Synapse
• Azure Event Hubs
• Strong understanding of relational databases, Data Warehousing and Data Lakehouse architectures.
• Knowledge of Master Data Management (MDM) concepts.
• Experience with Git, Azure DevOps, CI/CD pipelines and automated testing.
• Strong understanding of enterprise data governance practices.
• Proven experience working in fast-paced, high-touch client environments, managing conflicting priorities and ambiguity.
• Experience working within cross-functional POD structures and global delivery models.
• Demonstrable experience taking end-to-end ownership of technical deliverables rather than operating solely as part of a wider engineering team.
• Excellent stakeholder management and communication skills.

Desirable Experience

• Previous experience within a major Life Sciences or Pharmaceutical organisation, particularly across areas such as R&D data platforms, clinical/sample data, data fabrics or commercial analytics.
• Exposure to Generative AI frameworks, including LangChain, AutoGen or LlamaIndex.
• Experience integrating GenAI capabilities for data augmentation, automation or Root Cause Analysis (RCA).
• Microsoft Azure Data Engineer/DP-203 certification.
• Databricks Certified Data Engineer certification.