Mid/Senior Backend Data Engineer

Duration: Long termContract: B2B Rate: 160-170 PLN/h Mode: Remote 100% Summary: This role is critical for enhancing our data infrastructure, focusing on building and modernizing large-scale data processing systems to improve user experiences and operational efficiency. Main Responsibilities: • Implement and support large-scale data pipeline migrations. • Validate performance, reliability, and cost-efficiency of migrated workloads. • Contribute to the development of modern data processing stacks. • Utilize technologies like Flink and Lakehouse architectures. • Support production-grade data pipelines across the organization. • Collaborate with platform and infrastructure engineers in a fast-paced environment. Key Requirements: • Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. • Strong hands-on experience in backend engineering. • Very good knowledge of Java in data contexts. • Experience with JVM-based data processing frameworks (e.g. Flink). • Solid understanding of SQL and experience with cloud analytics (BigQuery). • Experience with containerized applications and basic Kubernetes knowledge. • Familiarity with cloud infrastructure in DevOps environments. • Experience in production-grade data pipeline development. • Ability to write high-quality, maintainable code. • Strong autonomy in ambiguous environments. Nice to Have: • 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. • Experience with data pipelines in Scala/Python. • Exposure to platform-level engineering. • Experience working in distributed engineering teams. • Prior experience in large-scale data pipeline migrations. • Familiarity with cost optimization in cloud-based workloads. • Experience with streaming platforms and Lakehouse architectures. Other Details: This role is part of a Data Infrastructure and Data Platform initiative, embedded within a Data Infrastructure team. The culture emphasizes collaboration, experimentation, and excellence in a cloud-native setup.