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

InPost; Warszawa, Kraków; Hybride; PLN 280 000 - 360 000; Plein temps

Avantages offerts par ce poste

Hybrid work model

B2B contract

Résumé du poste

InPost seeks a Staff Data Engineer for its Fintech Platform. You will own the feature-store architecture, anchoring the data engineering team and collaborating with the Head of Data Engineering and Head of ML.

You’ll design scalable pipelines, set governance standards, and drive high-impact data initiatives across regulated domains. Hybrid work with Warsaw/Kraków presence is offered.

Qualifications

• 8+ years in data engineering at scale.
• 5+ years in Spark/Databricks or equivalent lakehouse.
• Expert in SQL and Python (7+ years).
• Strong in data-quality, lineage and governance.

Responsabilités

• Design and own the feature-store architecture that supports credit decisioning.
• Set pipeline patterns, modelling standards and data lineage approach.
• Lead high-complexity data initiatives across regulated domains.
• Design agent loops for reliable, observable, cost-controlled engineering.

Connaissances

Data engineering

Spark/Databricks

SQL

Python

Data modeling

Observability

GDPR governance

Architectural leadership

Outils

Kafka

DBT

Structured Streaming

Databricks

Data pipelines

Description du poste

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

• Full-time

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.

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 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.
• 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.

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