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Intelligent Talent Solutions

Birmingham / Global

Data Engineer

  • £65,000
  • Remote

Job Summary

Salary Range:
£65,000
Work Settings:
Remote
Apply Now

Job Description

Data Engineer

Microsoft Fabric | Power BI | Azure | Data & AI

Remote UK, with 1-2 days per month in London or Birmingham

£55,000 - £65,000 + 10% bonus + 7% pension + benefits

Youve built your foundations as a Data Engineer. You can deliver without somebody constantly looking over your shoulder. Now you want more ownership and better exposure to where the Microsoft data platform is heading.

Thats the level this role is aimed at.

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

You wont have leadership or people-management responsibilities.

Instead, youll be trusted to take ownership of your own engineering work, from understanding the requirement and working through the technical problem to building, testing and deploying the solution.

What will you be working on?

The business is currently transitioning away from Azure Synapse, with the migration expected to complete by the end of the year.

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

Youll work alongside more experienced engineers across:

Building data pipelines in 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 Synapse solutions where needed during the transition

Youll have senior people around you when you need them, but this isnt a junior role.

They need somebody comfortable being given a problem, working through it and delivering a sensible production solution without requiring detailed instructions at every stage.

What do you need?

Microsoft Fabric and Power BI are essential.

Were looking for practical commercial experience with both, alongside a good grounding in Data Engineering.

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