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

Location: Hybrid in Warszawa or Kraków, Poland

Employment: B2B contract

Company

Build the data foundation for InPost Pay, a fintech scale-up within InPost, supporting financial decisions, credit, and data products.

What you will do

• Lead the Data Engineering & Analytics team, including hiring, coaching, performance management, and collaboration with Staff Engineers.
• Set the architecture direction for data pipelines, lakehouse systems, and feature stores supporting credit and decisioning products.
• Build a Databricks-based data platform with point-in-time correctness, freshness guarantees, lineage, and data-quality monitoring.
• Develop analytics for portfolio performance and unit economics in collaboration with Credit Risk and Data Product.
• Establish an AI-first engineering standard and production agent pipelines with guardrails, evaluation, observability, and cost and latency control.
• Own the platform roadmap, budget, tooling spend, and headcount planning with the Director of Data & AI and Data Product Lead.

Requirements

• 7+ years of experience as a Data Engineer and/or Architect.
• 3+ years leading data engineering or analytics engineering teams.
• 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, as well as budgets and roadmaps.
• Fluent English at B2+ level and availability for hybrid work in Warszawa or Kraków, Poland.

Nice to have

• Awareness of fintech regulations including CCD2, PSD2, and DORA.
• Credit-risk or underwriting data experience.
• Streaming or CDC experience.
• Experience scaling a data function through rapid growth.
• Vendor negotiation experience.

Culture & Benefits

• Leadership role with direct influence on architecture, engineering standards, and team development.
• Greenfield data platform with a modern Databricks lakehouse stack.
• Lean, AI-native organization with an emphasis on extreme ownership.
• Business-focused data function connecting engineering work to monetary value.
• B2B contract arrangement.