Data Platform Engineer
Role details
Job location
Tech stack
Job description
You'll work closely with BI, data product and governance colleagues to turn data from multiple source systems into well-engineered, production-ready datasets., You'll design, build and maintain ETL/ELT pipelines in the Microsoft cloud, primarily using Azure Data Factory, Databricks and related Azure services. Your focus will be on producing data pipelines that are robust, performant and cost-efficient, with quality and reliability built in from the start. You'll work with modern engineering practices - including Git, CI/CD and environment separation - to promote small, safe and frequent changes. You'll also play an active role in data quality, validation and governance, ensuring datasets are well-documented, secure and discoverable. Collaboration is key. You'll partner with BI analysts, data product teams and business stakeholders to ensure data is accessible, well-modelled and fit for purpose, supporting insight and decision-making across the organisation. "We're looking for engineers who care about quality and delivery. This role is about building data pipelines that are reliable, well-designed and genuinely useful - not just technically interesting. If you enjoy solving real problems and seeing your work used, this is a great opportunity." Christopher Heappey, Director of Insight & Innovation
Requirements
This role is for a hands-on engineer who enjoys building reliable, scalable data pipelines that people trust and use. As a Data Platform Engineer, you'll play a key part in delivering high-quality data into our cloud platform, enabling reporting, analytics and evidence-based decision-making across the organisation., You'll be a motivated data engineer with strong technical foundations and a practical mindset. You'll bring: Hands-on experience building ETL/ELT pipelines in a cloud environment Strong SQL skills and experience with data modelling Experience working with Databricks (PySpark/SQL) and Azure data services Familiarity with Git and CI/CD approaches for data engineering A collaborative approach and attention to detail You're proactive, methodical and comfortable working with both technical and non-technical colleagues. You take pride in building data solutions that are dependable, well-documented and ready for production use.