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

We are building a scale-up inside InPost. InPost Pay is growing from checkout into a full financial platform, and AI will flow through everything we do. This role is within a new business with executive backing, owning one of the few proprietary datasets in European payments where checkout, payment, and delivery behaviour meet.

• 8+ years leading data engineering or ML organizations and 5+ years managing managers or team leads
• Experience in financial services, payments or lending data platforms including lakehouse, feature store, and point-in-time-correct data serving
• Fluent and hands-on with Databricks/Spark at scale
• Hands-on experience with agentic systems in production
• Comfortable engaging with VP and C-level stakeholders
• Fluent in English (B2+)

Bonus points for:

• Regulated fintech or banking experience
• Experience scaling a data function from zero
• Vendor negotiation skills
• Multi-jurisdiction architecture experience

• Build agent-first systems with guardrails, evals, and observability as production components, not experiments
• Develop and maintain a state-of-the-art ML and MLOps stack on a governed Databricks lakehouse
• Create a unified data and ML platform including feature store, decisioning layer, and analytics
• Own data products with defined business cases, roadmaps, and measurable monetary outcomes
• Ensure decisioning in real-time with fast, explainable, and auditable credit and risk decisions
• Embed governance (GDPR, CCD2, and DORA) as a speed advantage to outpace competitors
• Foster a culture of experiments where every model and decision is tested and tied to business value
• Own budget, headcount, return on investment, and accountability for results
• Build from scratch the organization including Data Engineering & Analytics, ML & MLOps, Data Product teams
• Negotiate platform and tooling spend (including Databricks/lakehouse) and defend trade-offs at leadership level
• Report to the board on platform readiness, governance, and delivery risk
• Collaborate with staff and leadership teams on architecture and modeling patterns