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.
MissionToday there is no dedicated owner for business intelligence and analytics. Departments build their own reports directly on Salesforce (CRM and ERP), leading to inconsistent metric definitions and duplicated work. Databricks is in place as the data platform and Metabase is licensed for visualization, but neither is systematically used. The tooling exists; the foundation and ownership do not.
This role builds and owns the data function end to end: a single, trusted data foundation on Databricks, one definition per metric, and reliable financial, controlling, and operational reporting on top of it. It is a player-coach role. The first hire builds hands-on, then grows a small team.
Within 12 months, every financial, controlling, and operational number at Andercore comes from one governed data foundation, and every department can self-serve its core reports without building on raw Salesforce data.
Core responsibilitiesOwn the data platform: ingestion from Salesforce and other sources into Databricks, data modeling, quality, and documentation.
Build the metric layer: one definition per KPI (GMV, NRM, OTP, working capital metrics, and others), agreed with Finance and Operations, versioned and documented.
Deliver the three core report suites: financial reporting (CEO, CFO, board), controlling (FP&A), and operational reporting (supply, logistics, commercial).
Stand up Metabase as the single reporting front end and migrate departments off ad-hoc Salesforce reports.
Partner with Finance (FP&A), Operations, and Commercial as the go-to person for data questions; translate business questions into models and reports.
Prepare investor and board reporting data packs together with the CEO and CFO function.
Hire and manage one Data/BI Analyst once the foundation stands; define the longer-term team shape.
4-8 years in analytics engineering or data/BI roles, with clear hands-on depth: strong SQL, dbt (or equivalent transformation framework), and a lakehouse or warehouse platform, ideally Databricks.
Has built a metric or semantic layer before: can describe a project where they consolidated conflicting KPI definitions into one governed model.
Direct experience with the Salesforce data model as a source system, including its object model quirks and API/ETL constraints.
Understands the unit economics of a trading, distribution, or marketplace business: gross margin, net revenue margin, working capital, inventory or flow metrics. Physical goods, not pure SaaS.
Business-facing communication: comfortable in the room with a CFO or COO, able to push back on metric definitions and prioritize ruthlessly.
Player-coach mindset: wants to build hands-on for the first 6-12 months, then lead a small team.
Metabase experience (or a comparable BI tool such as Looker or Tableau, with willingness to work in Metabase).
German language skills (working language is English; German helps with some internal stakeholders).
Prior experience in a venture-backed scale-up between Series A and C.
Exposure to finance systems integration (ERP, accounting data, bank/payment data) for controlling and cash reporting.
First leadership experience (1-3 reports).
We are an equal-opportunity employer and welcome applicants from all backgrounds, regardless of race, ethnicity, gender identity or expression, sexual orientation, religion, age, disability, or any other characteristic. We believe that diversity drives innovation, creativity, and collective strength.
Skills Required
- Experience in BI and analytics roles
- Proven leadership in data management and AI implementation
- Strong skills in SQL and data warehousing
- Experience coaching and growing teams
What We Do
The company is the AI-driven trade platform transforming industrial supply in infrastructure, energy, and construction materials. It connects vetted suppliers across Asia, Europe, and the GCC region with local demand through a single integrated platform. Its proprietary AI stack digitizes and automates the full lifecycle of materials trade — from procurement and pricing to inventory, logistics, and embedded financing — replacing thousands of manual, relationship-driven processes with real-time orchestration. Buyers gain instant quotes, reliable availability, and predictable delivery through a unified operating system. Suppliers benefit from accurate forecasting, disciplined demand management, and seamless integration into cross-border fulfillment networks. The company partners with leading brands to run both dropship and cross-dock fulfillment motions for large-scale transactions, turning global supply chains into predictable, repeatable, software-like workflows. Backed by top-tier investors and institutional financing partners, the company has scaled to triple-digit-million GMV, operates across six international markets, and is rapidly expanding toward profitability. With a team of 80+ people across Berlin (HQ) and Asia, it is building the world’s first industrial-grade AI operating system for materials — redefining how global trade works in one of the world’s largest and most essential industries.









