Lead Data Engineer

Mindbox Sp. z o.o. KRAKÓW 2026-09-22

Strong hands-on experience with PySpark (DataFrame APIs, tuning, debugging).

Practical knowledge of Apache Iceberg, including:

- Optimisation techniques (partitioning strategy, file sizing, layout).
- Internal architecture understanding (snapshots, manifests, schema evolution).
- Maintenance operations (rewrite/compaction, orphan file cleanup, metadata handling).

Solid software engineering fundamentals: clean, testable, maintainable code, problem-solving.

Experience with CI/CD pipelines, observability, stability improvements in production systems.

Ability to work in global teams, excellent communication skills.

Ownership mindset and responsibility for end-to-end delivery.

Fluency in English (spoken & written).

Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.

At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe.

We are seeking an experienced Lead Data Engineer to join our client's global development team and drive the design and implementation of next-generation data platforms. You will work closely with teams in Poland, the UK, India, and China to enhance platform capabilities, improve performance, and ensure operational excellence.

Sounds like your kind of challenge?

#LI - Hybrid: 6/month form the office in Kraków

What you get in return

Flexible cooperation model

Hybrid work setup – 6/month form the office in Kraków

Collaborative team culture – work alongside experienced professionals eager to share knowledge

Continuous development – access to training platforms and growth opportunities

Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more

High quality equipment – laptop and essential software provided

,[Analyse and capture functional & non-functional requirements for near-term deliveries and long-term evolution., Design and implement data pipelines and table management workflows using PySpark and Apache Iceberg., Drive Apache Iceberg performance and cost optimisation (e.g., file sizing, partitioning, clustering, query efficiency)., Manage and improve Apache Iceberg maintenance (compaction, rewrite, snapshot/metadata management, orphan file handling)., Apply strong understanding of Iceberg internals (metadata layout, schema evolution, partition specs)., Ensure high engineering standards via code reviews, test automation, CI/CD, observability, and production readiness., Provide support for owned services and datasets, including on-call duties., Mentor and coach junior engineers; lead technical design discussions.] Requirements: PySpark, Communication skills, Apache Iceberg, CI/CD, DataFrame APIs