Backend Data Engineer

Xebia is a global tech company with origins in two Polish companies, PGS Software and GetInData, specializing in cloud, data, and software solutions. The company has over 1,000 experts working on projects across various industries including fintech, e-commerce, aviation, logistics, media, and fashion. Xebia partners with major clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, and InPost. The company uses modern open-source technology stacks and is a trusted partner of Databricks, dbt, Snowflake, Azure, GCP, and AWS, being the first AWS Premier Partner in Poland.

• Strong hands-on experience in backend engineering
• Very good knowledge of Java used in data platform or data engineering contexts
• Practical experience with at least one JVM-based data processing framework (e.g., Flink, Beam, Dataflow, Spark)
• Solid understanding of SQL and experience working with cloud-based data analytics platforms, particularly BigQuery
• Experience working with containerized applications and basic knowledge of Kubernetes
• Familiarity with cloud infrastructure as part of day-to-day DevOps work
• Experience working with production-grade data pipelines
• Ability to write high-quality, maintainable code and ship reliably to production
• Strong autonomy and ability to work effectively in an ambiguous environment without constant direction
• Experience with data engineering pipelines written in Scala and/or Python
• Previous exposure to platform-level engineering rather than only application-level development
• Experience collaborating within large, distributed engineering teams
• Practical experience using AI-powered assistants (e.g., Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery

Nice to have:

• Prior experience with large-scale data pipeline migrations
• Familiarity with cost optimization in cloud-based data processing workloads
• Experience working on or close to streaming platforms and Lakehouse-style architectures
• Interest in and familiarity with emerging AI-driven practices (e.g., agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches

• Implement and support large-scale data pipeline migrations as part of company-wide platform evolution efforts
• Validate performance, reliability, and cost-efficiency of migrated workloads
• Contribute to the development and evolution of a modern data processing stack, including streaming and batch processing platforms
• Work with technologies such as Flink-based platforms and Lakehouse architectures
• Support production-grade data pipelines used across the organization
• Collaborate closely with platform and infrastructure engineers in a fast-paced, execution-focused environment

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