Senior Data Engineer

In this role you design, build and run data pipelines and platform components to make data secure, reliable and ready for analytics. You will lead migration workstreams to Microsoft Fabric and establish foundations for analytics, self-service reporting and AI. You will set technical direction, coach engineers, and collaborate across Data Office, IT and business to deliver governed data and scalable data solutions. This position offers impact through data empowerment and cross-functional delivery in a growth-focused firm with a strong culture.

• flexible working options
• work life balance
• inclusive culture
• opportunity to contribute to social initiatives
• supportive leadership
• professional development

• Design, build and run data pipelines using Fabric Data Factory and Fabric Lakehouse with reusable patterns
• Own ingestion of data from core systems (Workday, Dynamics 365, Business World, SharePoint)
• Design data structures in Fabric Warehouse and Lakehouse for curated datasets used by Power BI and other reporting
• Incorporate security, data classification and access controls into pipelines and review others' work against them
• Redesign legacy ETL/ELT processes for Fabric and plan cut-over to maintain reporting continuity
• Establish version control, CI/CD and automated testing for data solutions; monitor pipeline performance and cost
• Coach and mentor less experienced engineers

• Proven experience delivering solutions on Microsoft Fabric (Data Factory, Lakehouse, Warehouse, Notebooks) or Databricks
• Strong Python, PySpark and SQL skills
• Solid understanding of data modelling, warehousing and ETL/ELT principles
• Experience delivering a platform or data migration
• Knowledge of Power BI integration with Fabric datasets
• Experience with Git and applying CI/CD to data solutions
• Knowledge of data governance, security and compliance including access control and data classification
• Experience migrating from Azure Data Factory and Azure Data Lake to Fabric
• Experience preparing data for AI use (RAG, vector databases, MCP) and processing unstructured data

• Clear communication with technical and non-technical colleagues
• Coaching or reviewing the work of less experienced engineers
• Curiosity and collaborative mindset
• Microsoft Fabric (Data Factory, Lakehouse, Warehouse, Notebooks)
• Databricks
• Python