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

InPost

Warszawa, Kraków

Hybrid

PLN 320,000 - 560,000

Full time

2 days ago
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Benefits offered by this job

Hybrid work model
B2B contract
Office in Warsaw/Kraków

Job summary

InPost is seeking an Architect for the data platform to design and own the feature-store architecture. You will be the technical authority shaping data engineering across the organisation, collaborating with the Head of Data Engineering and the Head of ML in a high-ambition scale-up.

This hands-on, individual-contributor role demands extreme ownership, end-to-end delivery, and governance with GDPR-aware practices, while working in a hybrid setup from Poland.

Qualifications

  • 8+ years in data engineering at scale.
  • 5+ years in Spark/Databricks or equivalent lakehouse architecture.
  • Strong SQL, data modelling and Python (7+ years).
  • Experience with agentic coding tools and loop engineering.
  • Staff-level engineer who sets standards through influence.

Responsibilities

  • Design and own the feature-store architecture that credit decisioning will depend on.
  • Set pipeline patterns, modelling standards and data lineage approaches.
  • Lead high-complexity, high-risk data initiatives across domains.
  • Design the agent loop (context, tools, evals, guardrails) for reliable, observable engineering.
  • Shape architecture to improve speed and quality of money-making decisions.

Skills

Data engineering
Spark/Databricks
SQL
Python
Agentic tools
Governance

Tools

DBT governance

Job description

  • Full-time
Company Description

Be the Architect the whole data platform is built around.

We are building a scale-up inside InPost, and AI will flow through it. You would be the anchor hire of the data engineering team: the technical authority whose design decisions every other engineer builds on. You'd work directly with the Head of Data Engineering and the Head of ML, with the InPost executive team backing the build. This is an individual-contributor role with organisation-wide scope. Your influence comes from your technical credibility, not your headcount. Our word is extreme ownership.

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