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Staff Data Engineer - Fintech Engineering (m/f/n)

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The mission
Design and own the feature-store architecture that credit decisioning will depend on.

  • Schema, point-in-time correctness and freshness SLAs, designed to be reliable and cheap to run.
  • Reference implementations. You set the pipeline patterns, modelling standards and lineage approach that others copy.
  • The hardest problems first. You lead the highest-complexity, highest-risk data initiatives, including cross-domain feature reuse across regulated entities.
  • Agent-first delivery. You design the agent loop (context, tools, evals, guardrails) so agentic engineering is reliable, observable and cost-controlled.
  • Data that earns. Your architecture directly shapes the quality and speed of money-making decisions.

You will own the architecture and inner workings of agentic harnesses and loop/graph agent workflows bound to the feature store: feature engineering, point-in-time validation, drift and data-quality observability. You set the reference patterns others reuse.

You are:

  • Someone who loves data and loves building systems around it.
  • Hands-on first. You design and you build, with AI as a daily tool.
  • Experienced with 8+ years in data engineering at scale, and 5+ years in Spark/Databricks or equivalent lakehouse architecture.
  • Expert in SQL, data modelling, and Python (7+ years), plus performance and cost engineering
  • Experienced with agentic coding tools and loop engineering (3+ years): context and tool design, evals, guardrails
  • Curious about advanced agentic harness, loop, and graph engineering, with deep knowledge of LLM behavior and trade-offs
  • A Staff-level engineer who sets standards through influence, not authority
  • Strong in data-quality, observability, lineage and GDPR-aware governance.
  • A technical leader without authority, who sets standards and mentors through influence.
  • Fluent in English (B2+).

Bonus points for:

  • Feature-store or ML data serving in production
  • Payments, fintech or lending data experience
  • Streaming (Kafka/Structured Streaming) and CDC
  • DBT governance experience.
  • CCD2/DORA awareness

Why this one:

  • Architectural authority from day one. You set the standard.
  • Greenfield, high stakes. Your design decisions last for years.
  • A modern stack and a lean, AI-native team.
  • Hybrid, ideally one day a week in the Warsaw or Kraków office.
  • We offer a B2B Contract

Skills

What Staff Data Engineering jobs ask for — and how much of it you have →
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See also

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