Head of Data Engineering & Analytics - Fintech Engineering (M/F/N)

About this role

The mission Build a data platform that works as a business asset, not a cost centre. Feature store and lakehouse on Databricks, with point-in-time correctness, freshness guarantees and full lineage. Data quality by default. Freshness, completeness and drift are monitored, and engineers are held to the standards you set. Analytics that move money. Portfolio performance and unit economics become decision-ready numbers, together with Credit Risk and Data Product.

Agent-first pipelines. Agents are production components, with guardrails, evals and observability, and you control their cost and latency. Governance as a speed advantage. GDPR-aware by design, audit-ready, and fast to ship. This is a business function. Every pipeline and every metric exists to create or protect monetary value. You will plan budget, tooling spend and headcount accordingly. What you'll own: The Data Engineering & Analytics team: hiring, coaching and performance, with Staff Engineers as your architectural anchors.

Pipeline and feature-store architecture direction for every data product that credit and decisioning depend on. The platform roadmap, co-authored with the Director of Data & AI and the Data Product Lead. The AI-first engineering standard across the team. You are: Someone with 7+ years of experience as a Data Engineer and/or Architect and 3+ years leading data engineering or analytics engineering teams. A leader who loves data and loves building systems around it.

Hands-on when needed , especially with AI on board. You understand every layer, from ingestion to serving. Proven in lakehouse and feature-store architecture at function scale. Experienced in data-quality, observability and lineage frameworks across a multi-team estate. Experienced in people management across Staff, Senior and Mid levels, plus budget and roadmap planning. Already building agentic systems in production.

Fluent in English (B2+). Bonus points for: Fintech regulation awareness (CCD2, PSD2, DORA) Credit-risk or underwriting data Streaming/CDC Scaling a data function through rapid growth Vendor negotiation experience Why join InPost? Seat at the table on a core leadership team. Greenfield with a real mandate. You set the architecture, the bar and the team. A modern stack. Databricks lakehouse from day one. Real pace. A lean, AI-native organisation.