Experienced Lead DevOps Engineer with a strong background in infrastructure management, Linux server administration, and automation. Extensive experience in leveraging Terraform for infrastructure as code (IaC) to manage complex deployments and maintain scalable, reliable cloud environments. Proficient in using Kubernetes and Microsoft Azure, with a deep understanding of Azure services, networking, and security. Highly skilled in troubleshooting and implementing observability solutions for complex systems. Proven team player with excellent communication and decision-making abilities. Responsibilities: • Responsible for leading Cloud Engineering team on new projects. • Guide and oversee the review and approval process of deployment plans and code reviews, ensuring technical feasibility and adherence to best practices • Lead initiatives of implementing best practices in infrastructure provisioning through terraform and create technical debt work items for the team. • Responsible for creating pipelines to deploy applications on Kubernetes cluster on Azure. • Collaborate with teams to address blockers impacting product deployment and provide timely solutions. • Manage and execute Cutover and Hypercare planning, and oversee the review of environment, infrastructure, and data plans • Worked on greenfield projects to get the infrastructure production ready through terraform. • Worked on creating Helm charts for deploying application on Kubernetes. • Worked on rolling out observability solution like Loki, Grafana, Promtail, Datadog, Azure insights for different project deployed on Kubernetes cluster and Linux server. • Worked on Microsoft Azure platform and AWS to support the existing microservice based solution. • Responsible for on call support for high priority issues Skills Set: ● Programming Language: Python, JavaScript, PowerShell, C#, Core Java, C, C++, R, JCL, CL, Cobol. ● Tools: Terraform, Jenkins, GitHub, Kubernetes, Docker, Jenkins, Automation Anywhere, IPCenter, Amelia, UiPath, Blue Prism, APICA. ● Cloud Platform: Microsoft Azure, Amazon Web Services(AWS) ● Data Analysis Tool: R Studio, SPSS, XL Miner, SAP BW/ERP ● Data Visualization: Tableau, Power BI ● Databases: Microsoft SQL Server, IBM DB2 ● Project Management Tools: Azure DevOps, Jira