Data Products & Management Director - Fintech Engineering (m/f/n)

About this role

The mission Build a data-first enterprise. Be the real business value layer of the company, owning both strategy and execution. Agent-first systems. Agents are production components with guardrails, evals and observability, not experiments. A state-of-the-art ML and MLOps stack. Models are built, validated, served and retrained properly, on a governed Databricks lakehouse. One data and ML platform. Feature store, decisioning layer and analytics sit on one foundation.

Data products with an owner and a number. Each one has a business case, a roadmap and a measurable monetary outcome. Decisioning in real time. Credit and risk decisions are fast, explainable and auditable. Governance as a speed advantage. GDPR, CCD2 and DORA are built in, so we ship faster than competitors, not slower. A culture of experiments. Every model and decision is tested, measured and tied to value. Every decision and every model carries monetary value, and you will run the function accordingly: budget, headcount, return on investment, and accountability for results.

What you'll own: The Data & AI strategy for our fintech build, and its delivery. The organisation, built from scratch: Data Engineering & Analytics, ML & MLOps, Data Product. You set the structure, the bar and who joins. The budget, including platform and tooling spend (Databricks/lakehouse), and the trade-offs you defend at leadership level. Board-level reporting on platform readiness, governance and delivery risk. Work with Staff and Leadership team on architecture and modeling patterns.

You are: A builder-leader. You love data and love building systems around it. Hands-on when needed, especially with AI on board. You understand every subsystem you lead, down to the detail. Someone with 8+ years leading data engineering or ML organisations and 5+ years managing managers or team leads. Experienced in financial services, payments or lending data platforms: lakehouse, feature store, point-in-time-correct data serving.

Fluent in Databricks/Spark at scale. Hands-on experience with agentic systems in production. At ease with VP/C-level stakeholders. Fluent in English (B2+). Bonus points for: Regulated fintech or banking experience Scaling a data function from zero Vendor negotiation Multi-jurisdiction architecture Why InPost? Seat at the table. Core leadership team, executive backing, extreme ownership. Real scope. First hire, your mandate, your organisation.