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Cazoo ищетSenior Data Engineer для удалённой работы в команде Data Engineering. Вы будете строить и обслуживать слои lakehouse, обеспечивать низкую задержку данных и тесное взаимодействие с продакт‑командамии, операторскими командами. Требуется опыт Databricks, Python и SQL.
Работа подходит для удалённой работы в условиях гибкого графика; участие в развитии платформа и данных для продуктов покупателей и продавцов.
Описание: Cazoo, is the ultimate destination for car enthusiasts and buyers alike! As a leader in the market, we pride ourselves on providing unparalleled search tools, expert car guides, insightful reviews, and a comprehensive vehicle price guide. Our mission is simple: to empower buyers to find their perfect car efficiently and with confidence, while also helping automotive retailers reach millions of eager buyers. At Cazoo, you'll be part of a team that's revolutionising the way people buy and sell cars. If you're ready to drive your career forward in a dynamic, fast-paced environment, Cazoo is the place for you. Join us and be a part of shaping the future of automotive retail! We are looking for Senior Data Engineer Reports To: Head of Data Engineering Contract Type: Permanent, Full Time Location: UK based, Remote 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 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. Highly desirable extras: deeper expertise in any of these will help you make an impact quickly. Deep Databricks know‑how, from performance and cost tuning to Unity Catalog governance, with hands‑on use of newer features such as Databricks Apps. Serving data to applications with Databricks Lakebase or, as an alternative, PostgreSQL tuned for read‑heavy workloads (schema design, indexing, query performance). Designing real‑time and event‑driven architectures that run in production, not just in a proof of concept. Advanced dbt: macros, packages, testing strategies and running it at scale. Data quality and observability practices, such as tests, data contracts and monitoring that catch issues before users do. Power BI, enough to design data that works well for the people building reports on it. Writing reusable Terraform modules and shaping how a platform is built as code. Experience in automotive, marketplaces, classifieds or other consumer‑facing digital platforms, where data shapes what customers see.