Data Engineer

Job description

About Us Lupa is building a category defining product the industry has never seen before. We're the AI-native operating system for veterinary practices and pet parents, replacing the fragmented, clunky systems vets have tolerated for years with a single intelligent platform for scheduling, client communication, clinical documentation, and AI-driven care guidance. Practices run more efficiently, vets get back to doing what they love, and pet parents feel more connected to their animals' health than ever. The traction speaks for itself: founded in 2023 and already one of Europe's top 100 AI startups, with a team of 50 people, 10x growth in twelve months, the UK market leader, and now charging hard into the US and Europe. We have $25M in funding, 1M+ pets on the platform, and a buzzing HQ in Paddington, London. We've attracted exceptional people from the likes of Palantir, Google, DeepMind, BCG, Meta, and AWS and we're just getting started. This is a rare chance to join a rocket ship at exactly the right moment and we're looking for exceptional people to help us fly it. In this role, you will: Design and build data pipelines from raw ingestion through to clean, modelled, production-ready datasets that engineering and product teams rely on Own data quality across your domain, defining standards, instrumenting checks, and resolving failures with urgency Monitor pipeline health in production and respond to issues proactively, not reactively Collaborate with engineering and product to understand data requirements and turn them into robust, scalable solutions Help define and evolve the architecture of our data platform as we scale across new geographies and product surfaces Document your work clearly so the team can understand, extend, and maintain what you build Your background looks something like: Multiple years of hands-on data engineering experience in a professional setting Strong Python skills and a demonstrated ability to build pipelines from scratch, not just extend existing ones Solid knowledge of data modelling and practical experience with Apache Spark, AWS services, Docker, and Airflow Experience in a startup or fast-growth environment where you’ve made pragmatic decisions under uncertainty Scala experience (nice to have, we’re happy to invest in teaching it if your foundations are strong) Familiarity with dbt, Delta Lake, or similar modern data transf…