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Fabric Data Engineer

Harnham - Data & Analytics Recruitment
Posted 14 days ago, valid for 6 days
Location

London, Greater London EC1R 0WX

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • The company is seeking a Fabric Data Engineer for an 8-month contract, offering a salary of £575-£625 per day (inside IR35).
  • The ideal candidate should possess strong experience with Python and SQL, along with practical knowledge of Azure Fabric and data services.
  • Key responsibilities include designing and deploying data pipelines, enabling data migration, and collaborating with stakeholders for data accuracy.
  • Candidates should have familiarity with DevOps practices and excellent communication skills to work in a cross-functional environment.
  • This role presents an opportunity to contribute to data transformation projects in a dynamic, insights-driven industry.

FABRIC DATA ENGINEER

8-MONTHS

£575-£625 PER DAY (INSIDE IR35)

This is a fantastic opportunity for a Data Engineer with Azure Fabric experience to contribute to a high-velocity organisation delivering cutting-edge data transformation projects. You'll take on a central role in building scalable, cloud-native pipelines and supporting reliable data flows across the business. This environment fosters autonomy, technical input, and exposure to modern data engineering approaches across a hybrid cloud ecosystem.

THE COMPANYThis global company operates in a dynamic, insights-driven industry, where data plays a critical role in shaping operations, customer intelligence, and strategic direction. The business is investing in a major infrastructure upgrade, shifting to Azure Fabric as part of its mission to modernise data delivery, enhance speed-to-insight, and unlock advanced analytics capabilities across international teams.

THE ROLEAs part of a forward-thinking engineering team, you'll contribute to the development of a robust data platform that supports both near-term reporting needs and longer-term transformation goals. You'll work on cloud migration efforts, streamline data access, and support cross-functional users with reliable, well-engineered solutions.

You'll be responsible for:

  • Designing and deploying efficient, resilient data pipelines within Azure Fabric

  • Enabling the migration of data from legacy systems and cloud services into the new Azure-based architecture

  • Working with technical and non-technical stakeholders to ensure data accuracy, completeness, and availability

  • Embedding automation and observability into workflows to enhance system stability and performance

  • Supporting both business-as-usual and greenfield data initiatives as part of an agile, collaborative team

KEY SKILLS & REQUIREMENTS

  • Strong experience with Python and SQL for data processing and transformation

  • Solid understanding of Azure data services, with practical experience in Azure Fabric

  • Knowledge of data streaming tools and real-time processing patterns

  • Familiarity with DevOps best practices, version control, and continuous integration pipelines

  • Excellent communication skills and the ability to operate effectively in a cross-functional environment

HOW TO APPLYIf you're interested in joining a forward-thinking organisation at a pivotal point in its cloud journey, please apply via the link on this page with your up-to-date CV.

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In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.