Head of Data Engineering & Analytics - Fintech Engineering (M/F/N)
InPost Krakow, Lesser Poland Voivodeship, Poland
Transportation, Logistics, Supply Chain and Storage · 10,001+ employees
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About the role
You will lead the Data Engineering & Analytics team to build a robust, AI-native data platform that serves as a critical business asset. Your role involves defining architectural standards, managing the team's performance, and ensuring data pipelines support financial decision-making and credit risk processes.
What they look for
Requirements
Candidates must have at least 7 years of experience in data engineering or architecture, with 3 years in a leadership capacity. Proficiency in lakehouse architectures, AI-driven systems, and managing multi-level engineering teams is essential.
Full description
Company Description
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.
Job Description
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.
Qualifications
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
Additional Information
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.
- We offer a B2B Contract
