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

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. 
• Real data at scale (17 million app users) that needs to be taken care of and translated into valuable decisions
• A lean, AI-native organisation where decisions take days or hours and concept of two-way door is well understood.
• We offer B2B type of contract