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

InPost Group; Kraków; Híbrido; PLN 600.000 - 840.000; Jornada completa

Descripción de la vacante

InPost Group is seeking a Head of Data Engineering & Analytics for Fintech Engineering. You will own the data foundation powering InPost Pay, leading a scale-up in a fast-moving, AI-driven environment.

You will manage architecture across data pipelines, feature stores, and governance, while guiding budget, tooling and headcount. The role combines hands-on work with strategic leadership in a fintech setting.

Formación

• 7+ years of experience as a Data Engineer and/or Architect.
• 3+ years leading data engineering or analytics engineering teams.
• Hands-on when needed, especially with AI on board.
• Proven in lakehouse and feature-store architecture at function scale.
• Experience with data-quality, observability and lineage frameworks.

Responsabilidades

• Lead the Data Engineering & Analytics team, hiring, coaching and performance management.
• Own pipeline and feature-store architecture for data products crediting decisioning.
• Shape the platform roadmap with the Director of Data & AI and Data Product Lead.
• Establish AI-first engineering standards across the team.

Conocimientos

Data engineering

Data architecture

Team leadership

Hands-on with AI

Budget & roadmap planning

Herramientas

Databricks

Feature store

Lakehouse architecture

Descripción del empleo

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 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.
• 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