Data Engineer (Databricks)

TL;DR

Data Engineer (Databricks): Designing, building, and maintaining end-to-end data pipelines for client reports and licensed datasets with an accent on Apache Airflow orchestration and PySpark processing. Focus on implementing AI-driven automation to streamline operational processes and ensuring high data quality through custom validation tooling.

Location: Hybrid (Warsaw, Poland). Must be based in the EU and possess a valid work permit.

Company

A global AI-first digital transformation and engineering partner with over 25 years of experience helping organizations build scalable data-driven solutions.

What you will do

• Design, build, and maintain end-to-end data pipelines for client-facing measurement reports and licensed datasets.
• Operate and troubleshoot Apache Airflow DAGs supporting scheduled and on-demand data deliveries.
• Implement automation and AI-driven agents to streamline operational processes and data validation.
• Develop data quality and validation tooling to ensure accuracy before client delivery.
• Write and maintain database migrations for delivery configurations and client setups.
• Collaborate with product, engineering, measurement science, and client-facing teams.

Requirements

• 2–4+ years of professional experience in Data, Software, or Operational Engineering.
• Experience with Databricks and PySpark for large-scale data processing.
• Strong proficiency in Python for building and debugging data pipelines.
• Hands-on experience with Apache Airflow (DAG development and troubleshooting).
• Very good knowledge of SQL, including complex joins and window functions.
• English: Upper-intermediate (B2) required.
• Location: Hybrid setup in Warsaw (once per week) and EU work permit required.

Nice to have

• Experience with Unity Catalog.
• Experience with database migrations and schema/version management.
• Comfort working in environments with frequent production support and delivery deadlines.
• Experience building agentic or AI-driven automation workflows.

Culture & Benefits

• People-first culture with a strong focus on engineering excellence.
• Consulting mindset combined with continuous growth and knowledge sharing.
• Opportunity to work with high-profile global clients like McLaren, Spotify, and Disney.
• Hybrid work model balancing remote flexibility and office collaboration.

Hiring process

• CV review followed by an HR call.
• Technical interview.
• Client interview.
• Final decision.