Analytics Engineer, Revenue, Purchase & Order

Brief info about Vinted Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life – or even a third. The Vinted Group is made up of three business units that support this mission: Vinted Marketplace is Europe’s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life. Vinted Go enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces. Vinted Pay is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members. Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people. Information about the position We are looking for an Analytics Engineer to join our Revenue, Purchase & Order Analytics Engineering team. The area sits at the heart of some of the most critical customer journeys and commercial systems across Vinted’s Marketplace Business Unit, spanning Revenue (pricing and advertising), Purchase (inquiries and checkout), and Orders (transactions and fulfilment). Together, these domains create a rich, high-volume, and deeply interconnected data ecosystem. As an Analytics Engineer, you’ll work at the intersection of data, engineering, and product, building trusted data products that power business and product decision-making across these domains. In this position, you’ll Build scalable data products: Design, develop, and evolve reliable, cost-efficient data products and pipelines that power analytics and machine learning use cases across the domains. Build quality in by design: Embed automated testing, validation, and quality controls throughout the data lifecycle to ensure data remains accurate, consistent, and complete. Strengthen observability: Improve monitoring and alerting to detect and address issue...

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