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

Be the Architect the whole data platform is built around. This role is part of a scale-up inside InPost with AI integration and works closely with the Head of Data Engineering, Head of ML, and the InPost executive team.

• Minimum 8 years experience in data engineering at scale.
• Minimum 5 years experience with Spark/Databricks or equivalent lakehouse architecture.
• Expert in SQL, data modeling, and Python (7+ years).
• Experienced with agentic coding tools and loop engineering (3+ years): context and tool design, evals, guardrails.
• Strong knowledge of data quality, observability, lineage, and GDPR-aware governance.
• Curious and deeply knowledgeable about advanced agentic harness, loop, and graph engineering, including LLM behavior and trade-offs.
• Staff-level engineer who sets standards through influence without formal authority.
• Fluent in English (B2+).

Nice to have:

• Feature-store or ML data serving in production.
• Experience with payments, fintech, or lending data.
• Experience with streaming (Kafka/Structured Streaming) and CDC.
• Experience with DBT governance.
• Awareness of CCD2/DORA practices.

• Design and own the feature-store architecture supporting credit decisioning.
• Ensure schema, point-in-time correctness, and freshness SLAs that are reliable and cost-effective.
• Provide reference implementations setting pipeline patterns, modeling standards, and lineage approaches.
• Lead complex, high-risk data initiatives including cross-domain feature reuse across regulated entities.
• Design the agent loop (context, tools, evals, guardrails) for reliable, observable, and cost-controlled agentic engineering.
• Own architecture and inner workings of agentic harnesses and loop/graph agent workflows bound to the feature store.
• Set reference patterns for feature engineering, point-in-time validation, drift, and data-quality observability.