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Andercore is an AI-native supplier of industrial materials for energy, infrastructure, and construction across seven European markets. The company operates a sophisticated trade and distribution platform powered by agentic AI, handling sourcing, quality, pricing, sales, logistics, and embedded financing. With $75M raised (Series B just closed) and strong triple-digit-million euro turnover, Andercore is redefining global materials trade.
This Data Lead role owns the analytics function end-to-end, building a single trusted data foundation that currently doesn't exist. Today, departments build ad-hoc reports directly on Salesforce, creating inconsistent metrics and duplicated work. Databricks and Metabase are licensed but not systematically used. You will establish governance, consolidate metric definitions, and enable self-service reporting across the organization.
Core responsibilities include: owning the data platform (Salesforce and other source ingestion into Databricks, data modeling, quality, documentation); building a metric layer with one definition per KPI (GMV, NRM, OTP, working capital); delivering three core report suites (financial for CEO/CFO/board, controlling for FP&A, operational for supply/logistics/commercial); standing up Metabase as the single reporting front end; partnering with Finance, Operations, and Commercial as the go-to data person; preparing investor and board reporting; and hiring/managing one Data/BI Analyst once the foundation is established.
This is a player-coach role: hands-on for the first 6-12 months, then growing a small team. Within 12 months, every financial, controlling, and operational number at Andercore comes from one governed data foundation.
Must-haves: 4-8 years in analytics engineering or data/BI roles with strong SQL, dbt (or equivalent), and lakehouse/warehouse experience (ideally Databricks). You've built a metric or semantic layer before and can consolidate conflicting KPI definitions. Direct Salesforce data model experience required, including object model quirks and API/ETL constraints. Understanding of trading, distribution, or marketplace unit economics (gross margin, net revenue margin, working capital, inventory/flow metrics—physical goods, not pure SaaS). Business-facing communication skills and comfort presenting to CFOs/COOs. Player-coach mindset.
Nice-to-haves: Metabase, Looker, or Tableau experience; German language skills; venture-backed scale-up experience (Series A–C); finance systems integration exposure; first leadership experience.
