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

Job Description

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.

Qualifications

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

Additional Information

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