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

Posted 6 Days Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Logistics • Transportation
The Role
Lead InPost Pay’s Data Engineering & Analytics function, owning team growth, architecture, platform roadmap, feature-store and lakehouse development, data quality, observability, lineage, analytics, AI-first engineering, governance, budgeting, and vendor planning. Build reliable data products supporting credit decisions, portfolio performance, unit economics, and production agentic systems while partnering with Data & AI, Data Product, and Credit Risk leadership.
Summary Generated by Built In
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

Skills Required

  • 7+ years of experience as a Data Engineer and/or Architect
  • 3+ years leading data engineering or analytics engineering teams
  • Hands-on understanding of data systems from ingestion through serving
  • Experience with lakehouse and feature-store architecture at function scale
  • Experience with data-quality, observability, and lineage frameworks across multi-team environments
  • Experience managing Staff, Senior, and Mid-level employees
  • Experience with budget and roadmap planning
  • Experience building agentic systems in production
  • Fluent English at B2+ level
  • Fintech regulation awareness, including CCD2, PSD2, or DORA
  • Credit-risk or underwriting data experience
  • Streaming or change data capture experience
  • Experience scaling a data function through rapid growth
  • Vendor negotiation experience
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The Company
HQ: Kraków
2,812 Employees
Year Founded: 2006

What We Do

InPost is the most successful operator of automated parcel lockers in Europe and also the one and only company in the world that is both a heavy operational user of APM machines as well as their manufacturer. InPost Parcel Lockers revolutionized the e-commerce delivery by providing a convenient way to send, collect and return parcels whenever the customer chooses, through a network of conveniently located and easy to use terminals.It is important for us to protect your personal data, our privacy policy can be found under the link: https://inpost.pl/ochrona-danych-osobowych

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