Data Engineer — PySpark, Airflow, Kubernetes (AWS)

Andersen; Kraków, Warszawa, Łódź, Lublin; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Private health insurance

Annual training budget

Referral program

Job summary

Andersen is seeking a Data Engineer in Kraków, Poland to build and maintain large-scale data pipelines and analytics platforms. You will work on processing audience and media data, deliver insights for advertising and consumer analytics, and ensure reliable data delivery.

The role requires Python and PySpark production experience, Airflow, and Kubernetes expertise. The position involves collaborating with cross-functional teams, migrating legacy processes to modern Kubernetes-native operators,

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• 5+ years as a Data Engineer.
• Production experience on AWS or Databricks.
• Strong Python and PySpark in production.
• Experience designing API-first services.
• Airflow in production.
• Kubernetes infrastructure management.
• Distributed data processing and orchestration.
• English upper-intermediate or higher.

Responsibilities

• Analyze and resolve pipeline failures and data integrity issues.
• Handle production incidents and operational tickets during shifts.
• Submit validated PRs with automated tests and concise summaries.
• Migrate legacy processes to Kubernetes-native operators; maintain Airflow compatibility.
• Refactor code to meet engineering standards.
• Support cross-functional integration with internal teams.

Skills

Python

PySpark

API-first

Airflow

Kubernetes

Distributed data processing

English (Upper-Intermediate+)

Education

Bachelor's degree in CS/Software Engineering or related

Tools

AWS

Databricks

Job description

Andersen is seeking a Data Engineer in Kraków, Poland to build and maintain large-scale data pipelines and analytics platforms. You will work on processing audience and media data, deliver insights for advertising and consumer analytics, and ensure reliable data delivery.

The role requires Python and PySpark production experience, Airflow, and Kubernetes expertise. The position involves collaborating with cross-functional teams, migrating legacy processes to modern Kubernetes-native operators,