Senior Data Engineer, Cazoo

• We don't expect you to tick every box. Strong fundamentals and the confidence to close gaps quickly matter more than any single tool
• Hands-on Databricks, Python and SQL: you've built and run production data pipelines on the platform, ideally on Azure, and can contribute from day one
• Working experience of Azure Data Factory and dbt, or similar orchestration and modelling tools you can transfer quickly
• Experience getting data to where it's used, beyond reports: serving it into operational systems and products, and supporting real-time data flows with tools such as Azure Event Hubs, Event Grid or Kafka
• Practical experience with infrastructure as code (Terraform) and CI/CD (Azure DevOps or GitHub)
• You use AI coding and agentic tools as a core part of how you work, with the engineering judgement to review, test and own what they produce
• Strong knowledge of neighbouring disciplines (analytics engineering, BI and MLOps), enough to work well across them
• Clear communication: you explain trade-offs to non-technical colleagues and build agreement across teams
• A growth mindset: you seek out feedback and act on it, you stick with hard problems and learn from setbacks, and you question inherited approaches rather than copying them

Desirable

• Help shape the future of Cazoo's data platform. Build real-time, product-facing data solutions with Databricks, Python and Azure in a fully remote Senior Data Engineer role
• Reports To: Head of Data Engineering
• We're looking for a Senior Data Engineer to join our small, fully remote Data Engineering squad, which runs the data platform behind Cazoo
• We're a highly engaged team built on three things: we own what we deliver, we look after each other and the teams we serve, and we never stop learning
• We've built a new data platform on Azure and Databricks, and it's stable and growing
• Our legacy estate is nearly retired, and we improved each flow as we moved it rather than copying it across
• Now the focus shifts to what the new platform makes possible
• That means operationalising analytics: getting trusted data out of the lakehouse and into the products our dealers and buyers use, often in real time, not just into reports
• You'll help build the low-latency serving and event-driven flows that make this work, and the new data products that come next
• This is a hands-on senior role
• You'll work with wide latitude on open-ended problems, lead work that crosses team boundaries, and help the engineers around you grow
• We back your professional development too, with room to progress as the platform does
• Design and build low-latency serving of lakehouse data into our internal and customer-facing products, working day to day with the feature teams who build them
• Build internal tools and data services on the platform that put trusted data directly in the hands of the teams who run the business
• Help shape how event data lands in our lakehouse, a pattern we're still defining
• Revisit and improve what we've migrated, paying down the shortcuts we took along the way and retiring any remaining legacy dependencies
• Turn requirements from analytics, product and engineering into reliable, well-modelled data products
• Take ambiguous problems from first question to production, making pragmatic trade-offs between speed and technical debt
• Extend our infrastructure as code, and keep CI/CD, testing and observability to a high standard
• Coach engineers through code review, pairing and onboarding, and take part in hiring
• Bring good practice in AI coding and agentic tools, helping the team use them well and safely
• Share in running what we build, including out-of-hours support for customer-facing data services

• We usually respond within two weeks