> Markdown version of [/jobs/ext/4699407-data-engineer-microsoft-fabric-azure](https://www.wearedevelopers.com/jobs/ext/4699407-data-engineer-microsoft-fabric-azure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Microsoft Fabric & Azure - **Company:** Intelligent Talent Solutions Ltd - **Location:** Birmingham, United Kingdom - **Experience:** Expert - **Salary:** £55,000 - £65,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Continuous Integration, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Database Queries, Python (Programming Language), Operational Databases, Power BI, Azure Data Lake, SQL Databases, Systems Integration, Data Processing, Azure Data Factory, Git, Microsoft Fabric, Pyspark, Azure Synapse Analytics, Data Pipelines - **Published:** November 13, 2026 - **Apply:** https://www.totaljobs.com/job/data-engineer/intelligent-talent-solutions-ltd-job108318045 ## About the Role The key requirement is genuine hands-on Microsoft Fabric experience in your current or most recent role. We're particularly interested in engineers who have worked with Fabric for at least 12 months and have experience supporting and improving solutions after they've been deployed into production. Alongside Fabric, we're looking for: * Strong SQL skills and practical data engineering experience. * Python and/or PySpark development experience. * Experience building and maintaining ETL/ELT pipelines. * Good knowledge of data modelling, transformation and validation. * Experience working with Azure Data Lake and other Azure data services. * Experience integrating data through APIs. * Familiarity with Git, Azure DevOps and CI/CD. * Confidence troubleshooting production issues and taking ownership of fixes. Experience with Power BI, Azure Synapse or regulated data environments would be beneficial. Previous financial services experience, particularly within banking, insurance or wealth management, would be welcome but isn't essential. The type of engineer we're looking for You don't need to have a Senior Data Engineer title or experience managing a team. What matters is that you're comfortable taking responsibility for your own engineering work, understanding the problem, developing a solution and making sure it continues to work reliably in production. You'll have experienced engineers around you for support and collaboration, but you'll also be trusted to work independently and make sensible technical decisions., If you're already working with Microsoft Fabric and enjoy the challenge of building, supporting and improving production data solutions, we'd be happy to tell you more. ## Description We're looking for a hands-on Data Engineer to join the growing data capability of an established UK wealth management business. The business is investing in Microsoft Fabric as it modernises its data platform, and needs an engineer who enjoys solving technical problems, building reliable pipelines and taking responsibility for what happens once solutions go live. This isn't a role where you'll simply build a pipeline and hand it over. You'll be involved in developing, maintaining, troubleshooting and improving the solutions you deliver. You'll join a small, experienced team, with the opportunity to take ownership of your work while continuing to develop your skills across Microsoft Fabric, Azure and modern data engineering. What you'll be doing You'll work on a mixture of new development, platform improvements and production support as the business continues its move from Azure Synapse to Microsoft Fabric. Your work will include: * Developing and maintaining Microsoft Fabric data pipelines, Lakehouses and data processing workloads. * Building ETL/ELT solutions using SQL, Python/PySpark and Azure technologies. * Working with Fabric Data Factory, OneLake, Warehouse and notebooks. * Integrating internal and external data sources, including APIs. * Developing data models, transformations and data quality controls. * Investigating production failures, identifying root causes and implementing lasting fixes. * Monitoring and optimising pipeline performance, reliability and efficiency. * Supporting existing Azure data services during the transition to Fabric. * Managing code, testing and deployments using Git, Azure DevOps and CI/CD. * Working with colleagues across engineering, analytics and the wider business.