> Markdown version of [/jobs/ext/4697491-data-engineer-microsoft-fabric-azure](https://www.wearedevelopers.com/jobs/ext/4697491-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:** London, United Kingdom
- **Salary:** £55,000 - £65,000
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Business Systems, Continuous Integration, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Python (Programming Language), Microsoft Data Access Components, Microsoft SQL Server, Power BI, Standard Sql, Azure Data Lake, SQL Databases, 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-job108318005

## About the Role

You'll already have commercial, hands-on Microsoft Fabric experience in your current or most recent role.

Importantly, we're looking for someone who has done more than simply help deliver a new platform. You'll understand the challenges of running data solutions in production, investigating problems and improving them as requirements change.

Ideally, you'll have spent at least 12 months working with Fabric in your current or most recent position, with responsibility for both development and ongoing support.

You'll also bring:

 * Strong SQL and data engineering skills.
 * Experience with Python and/or PySpark.
 * Good understanding of ETL/ELT, data modelling and data quality.
 * Experience with Fabric Lakehouse, pipelines, notebooks, OneLake or Warehouse.
 * Experience integrating data from APIs and other business systems.
 * Familiarity with Azure Data Lake and the wider Microsoft Azure data platform.
 * Experience with Git, Azure DevOps and CI/CD.
 * A practical approach to troubleshooting and supporting production systems.

Power BI and Azure Synapse experience would be useful. Previous experience in financial services, insurance or another regulated environment would also be an advantage.

You don't need to be a technical lead or manage other engineers. We're looking for someone who can take ownership of their own work, solve problems independently and contribute to a collaborative engineering team., If you're a hands-on Data Engineer with genuine Microsoft Fabric experience and enjoy taking responsibility for solutions beyond their initial delivery, we'd be pleased to hear from you.

## Description

Are you a Data Engineer working with Microsoft Fabric who enjoys building solutions but also wants to see how they perform once they're live?

We're recruiting for a UK wealth management business investing in its Microsoft data platform as it continues its transition from Azure Synapse to Microsoft Fabric.

This is an opportunity to join a small, experienced data team where you'll have genuine ownership of your work, exposure to modern data technologies and the chance to develop your skills without needing to move into a leadership role.

The role

You'll be working across the full lifecycle of data engineering solutions, from understanding requirements and developing pipelines through to deployment, production support and ongoing improvements.

The environment is centred on Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Factory pipelines and notebooks, alongside Azure Data Lake, SQL Server and Power BI.

Your responsibilities will include:

 * Building, maintaining and improving data pipelines using Microsoft Fabric and Azure.
 * Developing ETL/ELT workflows, data models and transformations using SQL and Python/PySpark.
 * Integrating data from internal systems and external sources, including APIs.
 * Monitoring production workloads, investigating failures and resolving underlying issues.
 * Improving pipeline performance, reliability, data quality and operational efficiency.
 * Supporting existing Azure Synapse workloads during the transition to Fabric.
 * Using Git, Azure DevOps and CI/CD to manage changes and deployments.
 * Working with engineers, analysts and business stakeholders to deliver reliable data solutions.