Head of Data Engineering & Analytics - Fintech Engineering (M/F/N)
Summary
Leadership role heading Data Engineering & Analytics for InPost Pay, a fintech scale-up inside InPost. You build and own the data platform end to end — Databricks lakehouse, feature store, data-quality and lineage, and production AI-agent pipelines — while hiring, managing the team, and planning budget and roadmap.
Head of Data Engineering & Analytics - Fintech Engineering (M/F/N)
- Contract
Own the data foundation that every financial decision at InPost Pay will stand on. We are building a scale-up inside InPost, and AI will flow through all of it. You would lead the engine room: from the first raw event to the feature that powers a decision to the report a board reads. You'd be a key member of the Data & AI leadership team, reporting to the Director of Data & AI, with the InPost executive team behind the build. Our word is extreme ownership.
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 Architectand3+ years leading data engineering or analytics engineeringteams.
- 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.
- Fintech regulation awareness (CCD2, PSD2, DORA)
- Credit-risk or underwriting data
- Streaming/CDC
- Scaling a data function through rapid growth
- 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.
- We offer a B2B Contract