Data Platform Engineering Manager (Cloud)

Power Media specializes in recruiting IT professionals and related industries since 1997, with headquarters in Wrocław. Since 2017, the company operates under the name IFIRMA SA but continues recruitment services as Power Media, serving clients in Poland and internationally.

• Minimum 7 years of experience in Data Engineering
• Minimum 3 years as Technical Lead or Manager of a Data Engineering team
• Experience designing and developing large Data Platforms in cloud environments
• Practical experience with at least one cloud solution: GCP (preferred), AWS, or Azure
• Strong knowledge of SQL and Python
• Experience with DBT or Dataform
• Practical knowledge of Data Warehouse and Lakehouse solutions
• Experience with BigQuery or Snowflake
• Experience building pipelines based on Event Driven Architecture and CDC
• Knowledge of Infrastructure as Code (Terraform)
• Experience implementing Data Governance and Security in cloud environments
• Experience collaborating with business and managing stakeholder expectations internationally
• Very good English language skills (minimum B2) for daily communication
• Willingness to travel monthly to Barcelona

Nice to have:

• Knowledge of Agile methodologies
• Familiarity with Dataproc and Datastream
• Experience with Data Mesh and Kappa architectures

• Design, develop, and maintain a modern, scalable cloud data platform
• Co-create Data Platform architecture and long-term data environment strategy
• Design efficient data pipelines and solutions based on Lakehouse and Data Mesh architectures
• Build real-time data processing and Change Data Capture (CDC) solutions
• Ensure high quality, security, and governance of data
• Mentor and develop a 9-person Data Engineering team
• Collaborate with architects, Data Scientists, and business stakeholders internationally
• Participate in key technology decisions and implement best Data Engineering practices
• Optimize platform performance, costs, and reliability

Work distribution:

• 50% hands-on Data Engineering
• 25% People Management
• 25% Process Management