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

Reads like a Data Leadership role: running a data team.

Warszawa/Kraków, Poland

Pay
Pay not listed
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Contract — employment source
Employment type in the employer’s posting: Contract
From the employer’s posting
Apply at InPost

What you’ll work on

Full posting
  • Lead hiring, coaching and performance for the Data Engineering & Analytics team

  • Direct pipeline and feature-store architecture for credit and decisioning data products

  • Co-author the platform roadmap with the Director of Data & AI and Data Product Lead

  • Set the AI-first engineering standard across the team

  • Plan budget, tooling spend and headcount for the data function

From the employer’s posting
The Data Engineering & Analytics team: hiring, coaching and performance
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 will plan budget, tooling spend and headcount accordingly.

Tools in this posting

  • Databricks
Source — Tool mentions in context
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.
- 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.

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Status in our records
Live
First seen by us
Oct 12, 2026 · 17 days ago
Recorded sightings
78
Last seen by us
Oct 29, 2026

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Job description

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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

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.

Source details

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Pay

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Location & working pattern

Warszawa/Kraków, Poland

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