Data Engineer – Data Platform

• Develop, implement, and optimize scalable data pipelines to ensure reliable and secure data flows
• Model and transform data according to modern best practices, including versioning, historization, and thorough documentation
• Develop and operate ETL and ELT processes, as well as orchestrated data pipelines
• Work with modern cloud technologies, preferably AWS, and support the continued expansion of the data platform
• Use Infrastructure as Code, ideally with Pulumi or Terraform, to ensure the stable and scalable evolution of the data platform
• Analyze and optimize data processes with regard to performance, scalability, stability, and data quality
• Work closely with Data Scientists, Analysts, Product teams, and Developers to support data-driven decision-making
• Actively contribute to the development of data engineering standards and the modernization of the BI and data landscape
• Develop a company-wide data foundation as a single source of truth for analytics and reporting
• Integrate, model, and transform data from different business areas, and operate a scalable analytics platform

• Several years of hands-on experience in Data Engineering, ideally in production cloud data platform environments
• Excellent knowledge of SQL and Python
• Experience with modern data stack technologies such as Snowflake, dbt, Prefect or Airflow, BigQuery, or comparable tools
• Experience with ETL/ELT processes, data modeling, and building robust data pipelines
• Experience with AWS or a comparable cloud platform
• Initial experience with Infrastructure as Code, ideally using Pulumi or Terraform
• Analytical thinking and the ability to communicate complex technical concepts clearly
• Independent, structured, and solution-oriented approach to work
• Openness to agile working methods, teamwork, and continuous improvement
• German language skills at least at B2 level and proficient English
• Residence in Germany is mandatory
• Nice to have: Experience in e-commerce or with marketplace and platform business models
• Nice to have: Knowledge of BI tools such as Looker, Tableau, or Power BI
• Nice to have: Experience with event streaming or distributed data architectures, such as Kafka or Spark
• Nice to have: Understanding of data quality, data governance, and monitoring
• Nice to have: Experience working with cross-functional product teams

• Full-time position
• Remote work options
• Work in a digital unit with a start-up atmosphere
• Contribute to customer-focused digital solutions, processes, and devices related to sports