Data Engineer (Databricks)

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

You will be:

• designing, building, and maintaining end-to-end data pipelines for client-facing measurement reports and licensed datasets,


• operating and troubleshooting Apache Airflow DAGs supporting scheduled and on-demand data deliveries,


• managing push-based delivery workflows (cloud storage, file transfers, delivery verification) Investigating and resolving production incidents across distributed systems (Airflow, databases, cloud storage),


• implementing automation and AI-driven agents to streamline operational processes and data validation,


• supporting custom delivery requests, including matching files, cross-reference datasets, and bespoke client configurations,


• developing data quality and validation tooling to ensure accuracy before client delivery,


• writing and maintaining database migrations for delivery configurations and client setups,


• collaborating with product, engineering, measurement science, and client-facing teams,


• documenting operational processes, runbooks, and delivery workflows.

Your profile:

• 2–4+ years of professional experience in Data Engineering, Software Engineering, or Operational Engineering,


• experience with Databricks and PySpark for large-scale data processing,


• strong proficiency in Python, including building and debugging data pipelines and automation scripts,


• hands-on experience with Apache Airflow (DAG development, operators, troubleshooting),


• very good knowledge of SQL, including complex joins, window functions, and JSON-based data,


• experience working with cloud platforms (AWS and/or GCP),


• upper-intermediate English,


• readiness to work in a hybrid setup (in the Warsaw office once per week).

Work from the European Union region and a work permit are 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.

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision