Data Devops - AWS

Job description

**Key Skills:** Containerization (Docker, Kubernetes), DevOps, Python, AWS, Kubernetes, GitHub **Roles and Responsibilities:** - Provide L3 support/ development for complex platform incidents escalated - Troubleshoot issues related to workspace provisioning, model execution, job orchestration, and data connectivity. - Perform root cause analysis (RCA) and implement permanent fixes for recurring issues. - Manage platform operations, including upgrades, patching, monitoring, and performance tuning & workspaces. Ensure uptime as a part of the KPI and SLA - Support data science environments (Python, R, Git) used by analytics and AI/ML teams. - Enable ML lifecycle activities including experimentation, training, and deployment. - Implement automation and monitoring improvements to enhance platform reliability. **Skills Required:** - Experience with Domino Data Lab - Data science platform support and ML workflow orchestration - Container and orchestration technologies such as Kubernetes, Docker - Code repository skills like GitHub, GitLab, Bitbucket - Cloud platforms such as Amazon Web Services - Amazon SageMaker - Microsoft Azure Machine Learning **Experience Requirements** - 7-10 years of overall IT experience - 4+ years supporting data science or analytics platforms - Experience in life sciences or pharmaceutical environments - Familiarity with regulated environments (GxP), ITSM tools, and change/release management. **Nice to Have** - Kubernetes administration/ Domino data lab certification - Cloud certifications (AWS/Azure) - Exposure to clinical analytics, research data platforms, or AI/ML model development. **Education:** Bachelor's Degree in related field