Rohith Goud
@rohithgoud
Experienced DevOps Engineer specializing in cloud infrastructure and automation.
What I'm looking for
I am a highly skilled DevOps and Cloud Engineer with over 6 years of experience in architecting, automating, and optimizing large-scale cloud infrastructures using AWS, Azure, and Google Cloud Platform. My expertise lies in CI/CD pipeline creation, infrastructure as code, and container orchestration, with a focus on secure, multi-cloud environments. I have a proven track record in building secure cloud solutions and implementing robust DevSecOps practices.
Throughout my career, I have developed complex scripts to automate infrastructure tasks and have successfully managed Kubernetes environments on AKS, EKS, and OpenShift. I am passionate about driving digital transformation and operational efficiency, and I actively stay current with evolving DevOps trends. My certifications in AWS, Azure, and Kubernetes, combined with my hands-on experience with a range of tools, enable me to mentor junior engineers and implement best practices across teams.
Experience
Work history, roles, and key accomplishments
DevOps Engineer - II
Nationwide
Feb 2023 - Present (2 years 5 months)
As a DevOps Engineer - II, I actively participated in Agile ceremonies, built and maintained web applications and APIs, and developed automation scripts for Azure and Kubernetes environments. I implemented CI/CD pipelines, managed Azure Kubernetes Service (AKS) clusters, and enforced DevSecOps principles to enhance security and compliance.
DevOps Engineer
Wipro
Jan 2018 - Jan 2022 (3 years 11 months)
In my role as a DevOps Engineer at Wipro, I engaged in Agile software development, built CI/CD pipelines, and automated deployment processes using Ansible and Terraform. I managed hybrid cloud infrastructures and implemented security best practices to ensure compliance and optimize costs.
Education
Degrees, certifications, and relevant coursework
Coventry University
Master of Science, Data Science
2022 - 2023
Completed a Master of Science in Data Science, focusing on advanced data analysis, machine learning, and statistical modeling techniques to derive insights from complex datasets.
Tech stack
Software and tools used professionally
Splunk
Microsoft Azure
Google Cloud Platform
Azure Storage
AWS Step Functions
GitHub
GitLab
SonarQube
Kubernetes
Azure Kubernetes Service
Azure Front Door
AWS CodePipeline
Jenkins
GitHub Actions
GitLab CI
DB
Gmail
.NET Core
.NET
Terraform
Azure DevOps
Jira
Java 8
Babel
Webpack
JavaScript
Java
PowerShell
Grafana
Kibana
Azure Monitor
OpenSearch
Ansible
AWS Lambda
Google Cloud Functions
Azure Functions
SQL
npm
Octopus Deploy
TeamCity
Thanos
Availability
Location
Authorized to work in
Skills
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