Founding Data Engineer – Agentic AI
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We're a Paris-based deeptech startup building the AI decision layer for European freight transport.
Large shippers spend hundreds of millions on transport every year, and most of those decisions still rest on spreadsheets and consulting slide decks. We replace that with a platform that combines a proprietary optimization engine and AI agents to cut freight costs by 5-15% and track carbon emissions in real time.
Why this role stands out
- Real traction from day one: €7M raised in pre-seed, and a CAC 40 group already live in production.
- A founding team that has done it before: a serial founder with a successful exit, two freight experts with 20+ years and 600+ optimization projects behind them, and a mathematician CTO who owns the solver.
- Founding role: you'll be our first data hire. You design the data foundations, set the standards and shape the team that follows.
- Hard, meaningful problems: messy enterprise data feeding optimization models and AI agents, with direct money and carbon impact for some of Europe’s largest companies.
What you'll build
- Ingestion pipelines that turn heterogeneous client data (TMS, ERP, carrier invoices, rate cards) into clean, reliable datasets.
- Data quality, normalization and reference data (carriers, locations, geocoding) that make fast client onboarding possible.
- The data layer powering our optimization engine and agentic workflows.
- Auditable carbon reporting (ISO 14083, CSRD).
What we're looking for
- 3+ years in data engineering, ideally in B2B SaaS with enterprise integrations.
- Strong Python, SQL and PostgreSQL, plus dbt and an orchestrator (Dagster, Airflow or Prefect).
- A builder mindset: you like blank pages, fast decisions and shipping.
- Bonus: experience with supply chain or logistics data, or with data pipelines for LLM and agentic systems.
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