data engineer in data platforms

Schwarz Digits develops and operates the technological foundation for digital decision-making across Europe. Its services include IT infrastructure, cloud, cybersecurity, data and AI, communication, and workspace solutions, supporting the digital transformation of companies and the Schwarz Group's retail, production, and environmental services businesses.

• Design, develop, and operate high-performance batch and streaming data flows in the central Google Cloud Data Lakehouse for analytics and machine-learning use cases;
• Optimize the GCP cloud architecture and ensure solution scalability;
• Advance data-processing standards for real-time and batch workloads;
• Apply modern software-engineering methods and improve CI/CD, automated testing, and deployment processes across the data organization;
• Support the development of central orchestration tools based on Airflow and dbt;
• Implement automated validation processes, including for streaming events;
• Ensure compliance with security and data-protection standards;
• Collaborate with Product Owners, Data Scientists, and business units to translate complex business requirements into technical solutions.

• Several years of solid experience in Data Engineering, Big Data, or Software Engineering, ideally in a senior role;
• Strong knowledge of cloud infrastructure, especially Google Cloud Platform;
• Deep experience processing real-time data with Apache Kafka;
• Very good knowledge of Python and Spark;
• Уверенное владение Kubernetes and Docker for containerization;
• Experience with the software-development lifecycle, Git, DevOps principles, and automated testing;
• Analytical thinking, an agile mindset, and an independent, solution-oriented approach;
• Very good English;
• Nice to have: Experience with Apache Airflow, dbt, modern architecture concepts such as Data Lakehouses and Data Mesh, German.

• Office role in Berlin, Germany.