> Markdown version of [/jobs/ext/4016992-data-engineer](https://www.wearedevelopers.com/jobs/ext/4016992-data-engineer). 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 - **Company:** ARC IT Recruitment - **Location:** London, UK - **Experience:** Expert - **Salary:** £85,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Microsoft Azure, Continuous Integration, Information Engineering, DevOps, Dimensional Modeling, Python (Programming Language), Machine Learning, Power BI, Standard Sql, DataOps, Star Schema, Data Management, Data Pipelines, Databricks - **Published:** October 30, 2026 - **Apply:** https://www.careerboard.com/gb/en/find-jobs-in-United-Kingdom/-345EF9E74F731B2E49/ ## About the Role * 5+ years in data engineering and building data pipelines * Strong Lakehouse and data management knowledge * Hands-on Azure experience: Data Factory, Databricks, Storage, DevOps * Strong Python and SQL * Dimensional modelling (star schema) for Power BI * Insurance or financial services data, MI or reporting experience * Solid grasp of CI/CD and data operations * Confident communicator, well organised and commercially minded Nice to have * ML model deployment experience * Infrastructure-as-code tooling ## Description Our client, an established financial services company, are looking to hire a Data Engineer to join the team. You'll take a hands-on role developing a cloud-based Lakehouse platform on Azure, helping analytics teams make faster and better-informed commercial decisions. They're looking for someone who enjoys both the technical build and working closely with the business., * Develop and enhance a central Lakehouse platform supporting pricing, risk and performance analytics * Build, test and deploy ELT pipelines and data products with strong governance * Assess the impact of change on the data model and handle new requests and incidents * Work with architects, analysts and engineers to maintain data standards and quality * Provide trusted, well-structured data for MI and reporting * Partner with data scientists to productionise ML models * Deliver improvements in an Agile/DevOps environment