Senior Product Specialist MES-1

Bayer is a global company involved in manufacturing environments and digital solutions, focusing on MES systems and cloud technologies.

• Degree in Computer Science, Software Engineering, IT, or a related field
• Strong hands-on experience with Kubernetes, Docker, and container orchestration
• Solid expertise in Terraform and Infrastructure-as-Code
• Strong experience with AWS cloud services (e.g., EKS, EC2, S3, IAM, networking)
• Hands-on experience in operations and monitoring tools (e.g., Prometheus, Grafana, CloudWatch, ELK or similar)
• Strong experience working in DevOps environments (CI/CD, Git, automated deployment pipelines, Helm charts)
• Strong understanding of system integration, APIs, and communication protocols
• Experience in manufacturing environments, MES systems (ideally PAS-X) and GxP is a plus
• Experience with Node-RED and OPC (UA/DA) for integration and automation
• Strong analytical and problem-solving mindset with a hands-on, operations-driven approach
• Fluent in English (written and spoken); German is a plus

• Design, build and operate MES solutions in cloud, including deployment, integration, scaling, and lifecycle management
• Manage and optimize containerized environments using Kubernetes, Docker, and Helm charts
• Automate infrastructure and deployments using Terraform and Infrastructure-as-Code principles
• Design and implement reliable and secure system integrations between MES, shopfloor equipment, and enterprise systems (e.g. SAP)
• Take ownership of operations, monitoring, and incident handling of MES platforms in production environments
• Implement and maintain monitoring solutions (logs, metrics, alerts, dashboards) to ensure system stability and performance
• Troubleshoot and resolve complex issues across MES, cloud, and integration layers
• Continuously improve operational processes, observability, and system resilience
• Collaborate with product teams and sites to deliver scalable, robust, and reusable MES solutions
• Contribute to standardization of deployment, operations, and monitoring practices across MES platforms