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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 €100M+ in annual turnover and $75M raised (Series B just closed), Andercore is redefining global materials trade.
You will be the first dedicated data platform engineer, owning the Databricks lakehouse end-to-end. Your responsibilities include:
- Manage ingestion pipelines from Salesforce and operational systems, with clean storage, pipeline architecture, orchestration, and governance
- Model the commercial and logistics domain (quotes, orders, margins, suppliers, shipments) into trusted datasets that finance, sales, procurement, and logistics teams rely on as a single source of truth
- Partner with the Head of Data to translate business questions into reusable datasets and metrics, moving away from one-off exports
- Build the data foundation for dynamic pricing, forecasting, and AI agents: features, signals, historical snapshots, and feedback loops
- Implement data quality observability through tests, monitoring, and alerting to catch broken pipelines and schema drift before they impact the business
- Add near-real-time processing where needed; keep batch processing where appropriate
You'll work within a 12-person product and engineering team where data is not a support function but directly drives the company's agents and margins. You'll have direct access to founders and commercial teams, with a clear path to leading a small data engineering team as the company scales. The role is hybrid in Berlin, with offices also in London, Mumbai, and Shanghai.
REQUIREMENTS:
- 5+ years of data engineering with real ownership of a platform (not just single pipelines)
- Deep expertise in SQL and Python, with hands-on Spark and lakehouse experience (Databricks/Delta Lake strongly preferred)
- Experience modeling messy operational data from CRM or ERP systems, including data edited manually by users
- Comfortable with infrastructure as code and software engineering practices for data (version control, CI, testing)
- Strong communication with non-technical stakeholders; ability to push back on requests and propose better solutions
- Proven ability to work in Series B environments with shifting priorities and incomplete specifications
- Proficiency using AI coding tools as part of your workflow
NICE TO HAVE:
- Streaming experience (Kafka, Kinesis, or equivalent)
- Machine learning and statistical analysis, especially for forecasting or pricing
- Salesforce expertise
- Background in commerce, marketplaces, or supply chain with interest in catalog, pricing, and fulfillment
- Degree in Computer Science, Engineering, or related field
