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Harrington Starr

GB / Global

Data Engineer

Job Description

Location: London

Are you a skilled Data Engineer with strong coding expertise and a passion for building scalable data solutions? We’re looking for a talented professional to join our team and play a key role in designing, developing, and optimising modern data platforms on Azure Cloud — with a focus on an exciting Microsoft Fabric implementation.

What you’ll do

  • Design and build robust data pipelines and ETL processes using Python and SQL.
  • Contribute to the rollout and optimisation of Microsoft Fabric, shaping the next-generation data platform.
  • Work across Azure services (Data Factory, Synapse, Databricks, Data Lake, Functions) to deliver secure and scalable data solutions.
  • Optimise data workflows for performance, reliability, and cost efficiency.
  • Collaborate with analysts, data scientists, and business stakeholders to ensure high-quality, trusted data is available for decision-making.
  • Implement best practices for data governance, monitoring, and CI/CD automation.

What we’re looking for

  • Proven experience as a Data Engineer or similar role.
  • Must have financial services experience
  • Strong Python coding skills and advanced SQL expertise (query optimisation, data modelling).
  • Hands-on experience with Azure data ecosystem (Data Factory, Synapse, Databricks, etc.).
  • Exposure to or keen interest in Microsoft Fabric and its integration into enterprise data strategies.
  • Solid understanding of data architecture, pipelines, and cloud-based ETL/ELT frameworks.
  • Familiarity with version control (Git) and CI/CD tools.
  • Strong problem-solving skills and the ability to work in an agile, collaborative environment.
  • Opportunity to be part of a Microsoft Fabric implementation, shaping a next-generation cloud data platform.
  • Work with cutting-edge Azure technologies and modern data engineering practices.

Apply now if you’re passionate about building modern data solutions with Python, SQL, Azure, and Microsoft Fabric, and help us deliver smarter, data-driven decisions.

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