Staff Data Engineer (Fintech)

Location: Hybrid, ideally one day a week in the Warsaw or Kraków office, Poland

Company

A scale-up inside InPost is building an AI-native data platform for credit decisioning and fintech applications.

What you will do

• Design and own the feature-store architecture supporting credit decisioning.
• Define schemas, point-in-time correctness standards, freshness SLAs, and cost-efficient operating patterns.
• Create reference implementations for pipelines, data modelling, and lineage.
• Lead high-complexity data initiatives, including cross-domain feature reuse across regulated entities.
• Design agent loops, tools, evaluations, context, and guardrails for reliable and observable agentic engineering.
• Own feature engineering, point-in-time validation, drift monitoring, and data-quality observability.

Requirements

• 8+ years of experience in data engineering at scale.
• 5+ years of experience with Spark, Databricks, or equivalent lakehouse architecture.
• Strong expertise in SQL, data modelling, Python, performance engineering, and cost optimisation.
• 3+ years of experience with agentic coding tools and loop engineering, including context and tool design, evaluations, and guardrails.
• Deep knowledge of LLM behaviour and trade-offs, data quality, observability, lineage, and GDPR-aware governance.
• Fluent English at B2+ level; hybrid availability in Warsaw or Kraków is expected.

Nice to have

• Production experience with feature stores or ML data serving.
• Payments, fintech, or lending data experience.
• Kafka, Structured Streaming, CDC, or dbt governance experience.
• CCD2 or DORA awareness.

Culture & Benefits

• Architectural authority and organisation-wide technical scope from day one.
• Greenfield development in a modern, AI-native environment.
• Close collaboration with the Heads of Data Engineering and ML and the executive team.
• Individual-contributor role with influence through technical credibility and mentoring.
• B2B contract offered.