Senior Data Platform Engineer

About Andercore Andercore is the AI-native supplier of industrial materials for energy, infrastructure, and construction in wholesale and beyond. We trade with global suppliers and distribute to European customers on our own account. Our AI runs the full trade and distribution end-to-end: sourcing, quality, pricing, sales, logistics, and embedded financing. For the customer, it feels like buying from their preferred local supplier; for our partners, it is the most convenient and safe way to do business across borders. Behind it, our software and agentic AI do the heavy lifting that used to take an asset-intensive supply chain with four or five intermediaries and weeks of manual coordination. Where we are today: Strong triple-digit-million euro turnover Seven European markets live 80+ people across Berlin (HQ), offices in London, Mumbai, and Shanghai $40M Series B just closed, $75M raised to date from Atomico, Project A, and Inven Capital, institutional financing from international banks. We are building the world's first and last industrial-grade AI operating system for materials, redefining how global trade works in one of the largest and most essential industries on earth. Why this role, why now We already run on Databricks, and we have a Head of Data who owns metrics, KPIs and business analytics. What's missing is the engineer who makes the platform solid: clean ingestion, a trustworthy model of our commercial and logistics domain, and a foundation ready for the next step, which is dynamic pricing and demand sensing. You'll be the first dedicated data platform hire. You'll set the standards the team grows into, with a path to leading a small data engineering team as we scale. What you will do Own our Databricks lakehouse end to end: ingestion from Salesforce and our operational systems, storage, pipeline architecture, orchestration and governance Model the commercial and logistics domain (quotes, orders, margins, suppliers, shipments) into clean, trusted datasets that finance, sales, procurement and logistics can all use without keeping their own version of the truth Work closely with our Head of Data to turn business questions into reusable datasets and metrics, not one-off exports Build the data foundation for pricing, forecasting and our AI agents: features, signals, historical snapshots and feedback loops that tell us whether a decision was right Make data quality observable: tests, monitoring and alerting, so broken pipelines and silent schema drift get caught before a buyer notices Add near-real-time processing where the business needs to act now, and keep things simple where batch is enough Who you are 5+ years in data engineering, with real ownership of a platform rather than a single pipeline Deep SQL and Python, plus hands-on experience with Spark and a lakehouse (Databricks strongly preferred: Delta Lake, Workflows, Unity Catalog) You've used a CRM or ERP as a primary source system and know what it means to model messy operational d