Senior Data Platform Engineer—Databricks & Lakehouse

HEINEKEN; Kraków; On-site; PLN 150,000 - 240,000; Full time

Job summary

HEINEKEN Kraków is seeking a Senior Data Platform Engineer to join the Global Platform Team. You will drive data processing frameworks, work with Databricks, PySpark, and SQL to build scalable pipelines across streaming and batch workloads.

You will collaborate with cross-functional teams, implement Delta optimization, and stay on the cutting edge of the Databricks lakehouse architecture, Unity Catalog, and declarative pipelines while contributing to a data-driven culture.

Qualifications

• 5+ years of experience in data/software engineering building data frameworks for large-scale processing.
• Excellent Python and software development skills, including OOP and testing with pytest/unittest.
• Ability to write elegant and maintainable code (pylint/pyright is a plus).
• Experience with Python libraries: Pydantic, SQLGlot.
• Proficiency building data pipelines with PySpark including performance observability and tuning.
• Databricks skills: building data pipelines (batch/streaming) using Lakeflow DLt and Job-based orchestration; Unity Catalog familiarity.

Responsibilities

• Design and build scalable data processing frameworks for streaming and batch workloads.
• Work on big data using PySpark and SQL, optimize pipelines and contribute to a modern Data Lakehouse built on medallion architecture.
• Collaborate with cross-functional teams to create seamless ETL/ELT processes and drive performance optimizations.
• Build efficient and scalable solutions leveraging Databricks features like Structured Streaming and Unity Catalog.
• Collaborate using Git in an agile environment and continuously refine the common code base.

Skills

Python programming

OOP principles

pytest/unittest

Git

Databricks

PySpark

Data pipelines

Tools

GitHub

GitLab

Azure DevOps

Unity Catalog

Job description

HEINEKEN Kraków is seeking a Senior Data Platform Engineer to join the Global Platform Team. You will drive data processing frameworks, work with Databricks, PySpark, and SQL to build scalable pipelines across streaming and batch workloads.

You will collaborate with cross-functional teams, implement Delta optimization, and stay on the cutting edge of the Databricks lakehouse architecture, Unity Catalog, and declarative pipelines while contributing to a data-driven culture.