Lead DevOps Engineer (GCP)
We are seeking a Lead DevOps Engineer with solid experience in designing, automating and supporting cloud-based infrastructure across GCP. The ideal candidate should be comfortable collaborating with development teams to enhance deployment processes, infrastructure reliability, scalability, security and operational efficiency.
This position requires hands-on experience with CI/CD pipelines, Infrastructure as Code, cloud services, containerization, monitoring and automation.
Responsibilities
- Design, build and maintain cloud infrastructure using GCP
- Implement and enhance CI/CD pipelines for application delivery
- Automate infrastructure provisioning and configuration through Infrastructure as Code
- Support containerized applications and cloud-native deployments
- Collaborate with development, QA, security and operations teams
- Enhance system reliability, scalability, performance and security
- Monitor production systems and assist with troubleshooting and incident resolution
- Define and promote DevOps best practices across engineering teams
Requirements
- Strong background as a DevOps Engineer or Cloud Engineer
- Hands-on expertise in at least one major cloud platform: GCP
- Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, Azure DevOps or similar
- Familiarity with Infrastructure as Code tools such as Terraform, CloudFormation, ARM/Bicep or Pulumi
- Practical experience with Docker and containerized environments
- Understanding of Kubernetes or cloud container services
- Hands-on work with monitoring, logging and alerting tools
- Strong scripting skills in Bash, Python, PowerShell or similar
- Solid understanding of networking, security and cloud architecture fundamentals
- Capability to work independently and support production environments
Nice to have
- Hands-on experience administering Kubernetes clusters
- Practical knowledge of Helm, Argo CD or GitOps practices
- Background in cloud security and compliance
- Exposure to serverless architectures
- Familiarity with cost optimization in cloud environments
