Data Engineer - Microsoft Fabric

If you’re already building with Microsoft Fabric and want more ownership of what happens to your solutions once they reach production, this role gives you that scope.

A UK Wealth Management business is moving its enterprise data platform from Azure Synapse towards Microsoft Fabric and is looking for another hands-on Data Engineer to join the team.

You won’t have leadership or people-management responsibilities. Instead, you’ll be trusted to take ownership of your own engineering work, from understanding the requirement and working through the technical problem to building, testing, deploying and supporting the solution.

You’ll have senior engineers around you when you need them, but this isn’t a junior role. What you’ll be working on

Microsoft Fabric is at the heart of where the data platform is going.

You’ll work across:

• Building data pipelines using Microsoft Fabric
• Fabric Lakehouse, Warehouse and OneLake
• Developing data models and analytics solutions
• Power BI development
• ETL/ELT
• SQL and SQL Server
• Azure Data Lake
• Internal and third-party API integrations
• Azure DevOps and Git
• CI/CD and production deployments
• Supporting existing Synapse solutions during the transition

The client isn’t looking for someone whose Fabric experience ends when a project goes live.

They want an engineer who has stayed close to the solutions they’ve built and understands the operational side of Data Engineering: supporting production services, investigating problems, making improvements and adapting solutions as requirements evolve., Ideally, you’ll have worked with Fabric for long enough to experience the full lifecycle rather than just the initial implementation. You should be able to talk about what you built, how it performed in production, issues you encountered and how the solution evolved.

The client would particularly value someone who has developed that experience over a sustained period. The emphasis is on genuine Fabric depth and longer-term ownership, rather than simply meeting an arbitrary number of years.

You’ll also need experience across several of the following:

• SQL
• Data modelling
• ETL/ELT development
• Azure data platforms
• Azure Data Lake
• API integrations
• Git/source control
• Azure DevOps
• CI/CD
• Developing, deploying and supporting production solutions

Azure Synapse would be useful but isn’t essential.

You’ll also need experience developing and deploying software or data solutions within a highly regulated environment.

Financial Services experience is strongly preferred, whether that’s Wealth Management, Banking, Insurance or another regulated financial organisation. Where AI fits

You don’t need to be an AI or Machine Learning Engineer.

The business is increasing its investment in AI, including Azure AI Foundry, and wants its engineers to become increasingly comfortable using AI as part of their work.

That might mean using Copilot or another LLM for code validation, debugging, documentation or other practical development tasks.

If you’ve done more than that, useful, but it isn’t a requirement.

You’ll have the opportunity to develop that experience alongside your core Data Engineering work. Technology environment

Data: Microsoft Fabric, Lakehouse, Warehouse, OneLake, Azure Data Lake, Azure Synapse Analytics: Power BI Engineering: SQL Server, SQL, ETL/ELT, API integrations Delivery: Azure DevOps, Git, CI/CD AI: Azure AI Foundry and wider Microsoft AI tooling

If you’re already working hands-on with Microsoft Fabric and have reached the point where you can deliver independently but still want to learn from experienced engineers, I’m happy to give you the full context on the team, platform and plans.