Senior Data Engineer (Cloud & ML Engineering) (B2B)

Responsibilities

• Join our international cloud engineering team driving innovation in the automotive industry.
• As a Senior Cloud Backend Engineer, you will design and implement a central cloud platform for scalable data processing pipelines using Kafka Streams, Java, and Azure Storage.
• You will build robust, cloud-native architectures capable of handling thousands of messages per second, ensuring real-time ETL, compliance, and data integrity at scale.
• Working alongside Software engineers, DevOps experts and cloud architects, you’ll ensure high availability, security, and reliability under the strict standards of the automotive sector.

Qualifications

• Successfully completed university degree in computer science, business informatics, mathematics, or a comparable field.
• 5+ years of experience in software/data engineering, cloud development, or ML engineering.
• Strong programming skills in Java, with solid knowledge of Spark, Kafka, and SQL. Python is a plus.
• Strong Proficiency in Azure Cloud, especially with Databricks, Azure DevOps, and IaC tools (Terraform, Helm, ARM).
• Experience with containerization and orchestration using Docker and Kubernetes.
• Familiarity with MLOps tools (MLflow, Azure ML, CI/CD pipelines).
• Passion for clean code, automation, and model explainability.
• Excellent communication skills in English.
• Openness to hybrid work model with occasional visits to our Katowice office.

About Cluster Reply

Cluster Reply is the Reply Group company specializing in consulting and system integration of Microsoft technologies. As a Microsoft partner, Cluster Reply is active in Germany, Austria and Switzerland and works within the Reply network with sister companies in Brazil, Great Britain, Italy as well as the USA. The company focuses on innovation and supports customers in their digital transformation. The solutions range from on-premises to cloud applications in the areas of modern workplace and security, business applications, applications and infrastructure as well as data and artificial intelligence.