Mid/Senior Backend Data Engineer

Duration: Long term

Contract: 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.