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About the role
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 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
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
Apply on employer site ↗
Warszawa/Kraków, PL
Posted 13 days ago