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

InPost; Warszawa, Kraków; In loco; PLN 420.000 - 620.000; Tempo pieno

Descrizione del lavoro

InPost Pay seeks a Head of Data Engineering & Analytics to own the data foundation powering all financial decisions. Lead the engine room from raw events to decision-ready features and reports, reporting to the Data & AI leadership team with a focus on extreme ownership.

You will shape the data platform as a business asset, drive budgeting for tooling and headcount, and set the architecture for lakehouse and feature-store implementations in a fintech context.

Competenze

• 7+ years as a Data Engineer/Architect and 3+ years leading data teams.
• Experience building lakehouse and feature-store architectures at scale.
• Strong data quality, observability and governance practices.
• Regulatory awareness in fintech (PSD2, DORA) is advantageous.

Mansioni

• Own the Data Engineering & Analytics function, including hiring, coaching and performance management.
• Define pipeline and feature-store architecture for data products used in credit and decisioning.
• Influence platform roadmap together with senior data leadership and product leads.
• Maintain an AI-first engineering standard across the team.

Conoscenze

Data engineering

Leadership

AI integration

System design

Mentoring

Formazione

Bachelor's or higher in CS/Engineering

Strumenti

Databricks

Airflow

SQL

Descrizione del lavoro

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