DevOps Engineer with 4+ years of experience in CI/CD pipeline optimization, AWS cloud deployments, and Kubernetes orchestration, driving faster, more reliable releases.
Overview
4
4
years of professional experience
1
1
Certification
Work History
DevOps Engineer
L & T Technology Services
08.2021 - Current
Managed end‑to‑end DevOps lifecycle for Volvo (Jenkins pipelines) and Allegion (GitLab Pipelines & AWS infrastructure), ensuring reliability and compliance
Built and optimized Amazon EKS clusters with auto‑scaling, RBAC, and secure networking, enabling reliable containerized workloads.
Provisioned and managed supporting infrastructure on AWS (EC2, VPC, RDS, IAM, CloudWatch) to ensure scalability, monitoring, and resilience.
Refined Infrastructure as Code (IaC) with Terraform, automating AWS provisioning and cutting manual effort by 70%
Configured SonarQube quality gates to fail builds on critical issues, reducing merge event build time and improving release confidence
Implemented Helm‑based release strategies with values.yaml and overrides, enabling environment‑specific and maintainable deployments
Automated testing with Python and Bash, reducing integration issues across GitLab, Jfrog Artifactory by 25%
Integrated BlackDuck and SonarQube scans with JIRA and GitLab, reducing time‑to‑remediation by 25% through faster developer feedback loops
Implemented and optimized GitLab CI/CD pipelines, introducing caching and build dependency management that reduced build time from 1 hr 10 mins to 30 mins, significantly accelerating deployments.
Enhanced observability with Grafana, Prometheus, and AWS CloudWatch, reducing MTTR and improving system reliability
Built Grafana dashboards to track KPIs such as CPU, memory, latency, and error rates, enabling proactive monitoring of AWS workloads
Leveraged BrowserStack for cross‑platform testing, cutting UI/UX defects in production by 35%
Integrated BlackDuck and coverage tools for license compliance and vulnerability scanning, strengthening DevSecOps practices
Implemented branching strategy and protections in GitLab, enforcing a structured flow (feature → dev → release → preprod → prod) to improve code quality and release discipline.
Documented workflows and best practices in Git, JIRA, and Confluence, improving collaboration and onboarding efficiency
Education
B. Tech - CSE
Lovely Professional University
01.2021
Skills
Programming and scripting: Python, Bash, Shell scripting,YAML
CI/CD tools: Jenkins, Azure DevOps, GitLab
Version control systems: Git, Gerrit, Azure Repos, Code Commit
Cloud infrastructure: AWS, Azure, Terraform
Containerization and orchestration: Docker, Kubernetes
Monitoring and logging tools: Grafana, Prometheus, Kibana