The project is part of a Data Analytics and Engineering program focused on building, optimizing, and operating scalable data pipelines to support analytics, reporting, and data-driven decision-making across the organization.

• Design, build, and maintain efficient data pipelines for collecting, transforming, and storing data
• Integrate data from various sources, including cloud platforms (Google Cloud), SQL/NoSQL databases, APIs, and external services.
• Optimize and troubleshoot existing pipelines to ensure high performance and reliability.
• Implement ETL processes to transform raw data into analytics-ready datasets.
• Collaborate with cross-functional teams (data engineering, operations) to understand data requirements and deliver solutions.
• Support data applications when required during weekends or non-office hours
• Build scalable, automated workflows capable of processing large data volumes with low latency.
• Set up monitoring and alerting for data pipelines to minimize downtime
• Create and maintain technical documentation for data flows and pipeline configurations

• 5 - 10 years of experience as a Data Engineer, Dataflow Engineer, or in a similar role working with large-scale data systems
• Strong programming skills in Python and Java
• Hands-on experience with data pipeline orchestration tools (e.g., Google Dataflow)
• Solid experience with Google Cloud Platform, including BigQuery and Dataflow
• Strong background in ETL frameworks, real-time data streaming, and data processing
• Experience with SQL and NoSQL databases
• Knowledge of data governance, data quality, and data security best practices
• Strong problem-solving and troubleshooting skills
• Fluent English and Polish

• Experience with additional cloud services or multi-cloud environments
• Familiarity with data formats such as JSON, Parquet, or similar
• Experience building highly available, low-latency data pipelines
• Exposure to on-call or out-of-hours support models
• Strong communication skills and experience working with both technical and non-technical stakeholders