Senior GCP Devops

Sdna Global; Hyderabad, Chennai District, Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Sdna Global in Hyderabad, India is seeking an experienced cloud & DevOps engineer to design and manage scalable CI/CD pipelines and containerized ML workloads. You will implement IaC using Terraform and Helm, govern access with GCP IAM, and operate Kubernetes clusters in a distributed cloud environment.

Applicants should master Git-based workflows, Helm packaging, Istio/service mesh, and modern CI tools to enable secure, automated deployments across multiple regions.

Qualifications

• Strong understanding of CI/CD pipelines in distributed environments.
• Experience with Git, Artifactory, Jenkins, and Docker registries.
• Hands-on with GCP IAM for roles and access control.
• Kubernetes expertise including Helm charts for packaging.
• Terraform Enterprise proficiency and reusable modules.

Skills

CI/CD pipelines

GCP IAM

Infrastructure as Code

Cloud architectures

Microservices

ML workloads

Kubernetes

Terraform

Helm

Git

Tools

Git

Artifactory

Jenkins

Docker

Terraform Enterprise

Terraform

Helm

Kubernetes

Istio

Harness

Job description

Required Skills and Experience

Strong understanding of CI/CD pipelines in a globally distributed environment using Git,

Artifactory, Jenkins, and Docker registry.

Experience working with GCP IAM to manage roles, permissions, and secure access to

cloud resources.

Hands-on knowledge of Helm charts for packaging and deploying applications in

Kubernetes.

Hands-on experience deploying and managing Kubernetes infrastructure using

Terraform Enterprise, including the ability to write reusable Terraform modules.

Experience implementing infrastructure as code and orchestrating cloud infrastructure in

scalable, automated ways.

Knowledge of core GCP services and how they integrate within modern cloud

architectures.

Working knowledge of Istio or similar service mesh technologies.

Experience deploying and troubleshooting microservices in distributed environments.

Hands-on experience with Kubernetes and Docker for containerised ML workloads.

Experience using Terraform and Helm to manage ML infrastructure and deployment

pipelines.

Experience designing and managing CI/CD pipelines using tools such as Harness for

model build