AWS Platform Engineer – Data Science & MLOps

Help develop and operate an enterprise platform supporting Analytics, Data Science and Machine Learning teams. The environment combines AWS, Kubernetes, infrastructure automation and Domino Data Lab to provide secure, reliable and scalable development capabilities. You will combine hands-on platform engineering with requirements analysis, stakeholder coordination and operational support, working closely with business, product, infrastructure, security and vendor teams. Your responsibilities Translate business and technical requirements into user stories, acceptance criteria and delivery priorities. Contribute to technical design discussions, architecture reviews and stakeholder workshops. Develop and maintain platform features, integrations and deployment frameworks. Manage and optimise AWS resources and EKS/Kubernetes environments, including networking, storage, IAM, security and monitoring. Automate infrastructure and configuration using Terraform and Ansible, and improve deployments through GitHub, GitOps and CI/CD. Enable and support Domino Data Lab and Python- and R-based development environments. Coordinate deployments across Development, Test and Production, supporting release planning and change management. Monitor platform health, troubleshoot production incidents, perform root cause analysis and implement preventive improvements. Support system integration testing, user acceptance testing, regression, performance and operational testing, including defect resolution. Maintain technical specifications, deployment guides, operational procedures and knowledge repositories. Ensure platform changes and operations follow enterprise security, governance, audit and data protection requirements.

Requirements Help develop and operate an enterprise platform supporting Analytics, Data Science and Machine Learning teams. The environment combines AWS, Kubernetes, infrastructure automation and Domino Data Lab to provide secure, reliable and scalable development capabilities. You will combine hands-on platform engineering with requirements analysis, stakeholder coordination and operational support, working closely with business, product, infrastructure, security and vendor teams. Your responsibilities Translate business and technical requirements into user stories, acceptance criteria and delivery priorities. Contribute to technical design discussions, architecture reviews and stakeholder workshops. Develop and maintain platform features, integrations and deployment frameworks. Manage and optimise AWS resources and EKS/Kubernetes environments, including networking, storage, IAM, security and monitoring. Automate infrastructure and configuration using Terraform and Ansible, and improve deployments through GitHub, GitOps and CI/CD. Enable and support Domino Data Lab and Python- and R-based development environments. Coordinate deployments across Development, Test and Production, supporting release planning and change management. Monitor platform health, troubleshoot production incidents, perform root cause analysis and implement preventive improvements. Support system integration testing, user acceptance testing, regression, performance and operational testing, including defect resolution. Maintain technical specifications, deployment guides, operational procedures and knowledge repositories. Ensure platform changes and operations follow enterprise security, governance, audit and data protection requirements. What we are looking for Hands-on experience engineering and supporting AWS environments. Practical Kubernetes experience, ideally with Amazon EKS, including deployment, operation and troubleshooting. Experience with Terraform, Ansible and infrastructure automation. Working knowledge of GitHub, GitOps and CI/CD pipelines. Python skills for automation and integrations, with familiarity supporting Python and R development environments. Experience delivering technical changes through development, testing, deployment and production support. Understanding of change, release and incident management. Ability to analyse requirements, write clear user stories and acceptance criteria, and coordinate business and technical stakeholders. Awareness of enterprise security, governance and GxP validation expectations. Ability to produce clear technical and operational documentation. An advantage Experience administering, integrating or supporting Domino Data Lab. Experience supporting enterprise Data Science or Machine Learning platforms. Experience with GxP validation and controlled releases in pharmaceutical or other regulated environments. Technology stack AWS

• Amazon EKS
• Kubernetes
• Terraform
• Ansible
• GitHub
• GitOps
• CI/CD
• Python
• R
• Domino Data Lab

Benefits Location: Prague or another EU country Contract Type: Freelance / Contract Start date: November/December 2026 Time Allocation: 40 hours/week Pharmaceutical company in Prague