Senior Data Engineer with Databricks (Warsaw) New Poland

Xebia Group; Warszawa; Hybrid; PLN 200,000 - 320,000; Full time

Job summary

Xebia Group in Warsaw is seeking a Senior Data Engineer with Databricks to design, build and maintain scalable data ingestion and transformation pipelines. You will work across Bronze, Silver, Gold layers and contribute to data product delivery.

The role requires strong SQL, hands-on Databricks experience, cloud ETL/ELT, and collaboration with data modelers and BI engineers. EU work permit and work from EU region apply.

Qualifications

• Strong hands-on experience building data pipelines and transformation solutions.
• Hands-on experience with Databricks.
• Strong SQL skills and experience working with large-scale datasets.
• Experience implementing ETL/ELT processes in cloud environments.
• Experience developing data integration and transformation frameworks.
• Familiarity with Bronze, Silver, and Gold data layers.
• Experience with automated testing, reconciliation, and data quality processes.
• Knowledge of software engineering best practices, version control, and CI/CD.
• Ability to work in cross-functional delivery teams.
• Strong analytical, troubleshooting, and problem-solving skills.
• Effective communication and stakeholder collaboration skills.
• Work from the European Union region and a work permit are required.

Responsibilities

• Designing, developing, and maintaining scalable data ingestion and transformation pipelines.
• Building metadata-driven data processing frameworks and reusable engineering components.
• Developing and maintaining data flows from landing, Bronze, and Silver layers through analytical consumption layers.
• Creating and optimizing ETL/ELT processes supporting enterprise data products.
• Implementing reconciliation, data validation, and automated testing capabilities.
• Supporting development of data product delivery frameworks and engineering templates.
• Participating in source-focused and domain-focused delivery pods.
• Collaborating with data modelers, BI engineers, platform engineers, architects, and client stakeholders.
• Supporting migration of legacy data processing workloads and analytical assets.
• Developing monitoring, logging, and operational support mechanisms for data pipelines.
• Contributing to CI/CD-driven engineering practices and automation initiatives.
• Supporting knowledge transfer and handover activities to client engineering teams.
• Participating in data quality, troubleshooting, and performance optimization activities.

Skills

Databricks

SQL

Data pipelines

ETL/ELT

Cloud environments

CI/CD

Data architecture

Data quality

Cross-functional collaboration

Communication

Version control

Tools

Databricks Asset Bundles (DABs)

dbt

Job description

Senior Data Engineer with Databricks (Warsaw)

Poland

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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, 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, developing, and maintainig scalable data ingestion and transformation pipelines.
• - Building metadata-driven data processing frameworks and reusable engineering components.
• - Developing and maintaining data flows from landing, Bronze, and Silver layers through analytical consumption layers.
• - Creating and optimizing ETL/ELT processes supporting enterprise data products.
• - Implementing reconciliation, data validation, and automated testing capabilities.
• - Supporting development of data product delivery frameworks and engineering templates.
• - Participating in source-focused and domain-focused delivery pods.
• - Collaborating with data modelers, BI engineers, platform engineers, architects, and client stakeholders.
• - Supporting migration of legacy data processing workloads and analytical assets.
• - Developing monitoring, logging, and operational support mechanisms for data pipelines.
• - Contributing to CI/CD-driven engineering practices and automation initiatives.
• - Supporting knowledge transfer and handover activities to client engineering teams.
• - Participating in data quality, troubleshooting, and performance optimization activities.

Your profile:

• Strong experience building data pipelines and transformation solutions.
• Hands-on experience with Databricks.
• Strong SQL skills and experience working with large-scale datasets.
• Experience implementing ETL/ELT processes in cloud environments.
• Experience developing data integration and transformation frameworks.
• Familiarity with modern data architecture concepts, including Bronze, Silver, and Gold layers.
• Experience with automated testing, reconciliation, and data quality processes.
• Knowledge of software engineering best practices, version control, and CI/CD principles.
• Ability to work in cross-functional delivery teams.
• Strong analytical, troubleshooting, and problem-solving skills.
• Effective communication and stakeholder collaboration skills.
• Work from the European Union region and a work permit are required.

Nice to have:

• Experience with metadata-driven processing frameworks.
• Familiarity with data product-oriented architectures.
• Knowledge of dbt or modern analytics engineering practices.
• Experience working with Databricks Asset Bundles (DABs) and deployment automation.
• Experience with Infrastructure as Code and cloud-native data platforms.
• Exposure to GxP-regulated environments.
• Experience supporting large-scale data modernization or migration programs.
• Knowledge of reconciliation automation and enterprise data governance practices.
• Experience mentoring junior engineers and contributing to engineering standards.

Recruitment Process:

CV review - HR call - Interview - Client Interview - Decision