Senior Data Engineer with Databricks (Warsaw)

Opis oferty

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. 

 

Wymagania

• 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. 
• Experience delivering solutions in enterprise-scale environments.
• Work from the European Union region and a work permit are required.

Zakres obowiązków

• - 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.