Data Engineer

In this role you will design and operate data pipelines and platform components to ensure secure, reliable data for analytics and reporting. You will contribute to migrating to Microsoft Fabric and lay the foundations for analytics, self-serve reporting, and AI capabilities. You’ll work with the Data Architecture team to align with standards and drive milestones in data tooling. This is a hands-on role at scale, with a focus on governance and quality, enabling analysts to reuse certified datasets and insights. You join a culture that values inclusion, curiosity, and impact, helping redefine how data supports clients and the firm.

• flexible working options
• work life balance
• inclusion and supportive culture
• opportunity to contribute to society
• career development
• ambitious growth environment

• Build and run data pipelines and notebooks in Fabric using Data Factory, Lakehouse, Python, PySpark and SQL
• Ingest data from core systems (Workday, Dynamics 365, Business World, SharePoint)
• Create and maintain data structures in Fabric Warehouse and Lakehouse and deliver certified datasets for Power BI
• Prepare governed data for AI, including retrieval via RAG and MCP, and convert PDFs into structured form
• Enforce data classification, access control and segregation standards in all work
• Migrate existing Azure Data Factory/ADL/SQL Server solutions to Fabric and redesign ETL/ELT
• Apply CI/CD, version control, automated testing and monitoring to pipelines
• Keep up to date with Fabric features and document learnings
• Ensure pipelines run reliably, meet migration milestones, and produce reusable datasets for analysts

• Practical experience with Microsoft Fabric (Data Factory, Lakehouse, Warehouse, Notebooks) or Databricks
• Proficiency in Python, PySpark and SQL for data engineering
• Understanding of data modelling, warehousing and ETL/ELT principles
• Working knowledge of Power BI and version control (Git/DevOps)
• Awareness of data governance, security, and compliance best practices
• Ability to manage own workload and communicate clearly with technical and non-technical colleagues

• ambition and drive
• curiosity and proactive questioning
• clear communication with both technical and non-technical stakeholders
• Microsoft Fabric (Data Factory, Lakehouse, Warehouse, Notebooks)
• Databricks
• Python