Sr GCP Engineer

3+ years of experience as a DevOps Engineer or Cloud Engineer, with hands-on experience in managing cloud infrastructure. Proven experience working with Google Cloud Platform (GCP) services such as Compute Engine, Cloud Storage, Kubernetes Engine, Pub/Sub, Cloud SQL, and others. Experience in automating cloud infrastructure with Infrastructure as Code (IaC) tools like Terraform, Cloud Deployment Manager, or Ansible. Strong knowledge of CI/CD tools and processes (e.g., Jenkins, GitLab CI, CircleCI, or GCP Cloud Build). Proficiency in scripting and automation using Python, Bash, or similar languages. Strong understanding of containerization technologies (Docker) and container orchestration tools like Kubernetes. Familiarity with GCP networking, security (IAM, VPC, Firewall rules), and monitoring tools (Stackdriver). Experience with Git for version control and collaboration. Knowledge of security best practices for cloud environments, including IAM, network security, and data encryption. Understanding of compliance and regulatory requirements related to cloud computing (e.g., GDPR/CCPA, HIPAA, or PCI).

Design, implement, and maintain scalable, reliable, and secure cloud infrastructure using GCP services. Automate cloud infrastructure provisioning, scaling, and monitoring using Infrastructure as Code (IaC) tools such as Terraform or Google Cloud Deployment Manager. Manage and optimize GCP resources such as Compute Engine, Kubernetes Engine, Cloud Functions, and BigQuery to support development teams. Build, maintain, and enhance continuous integration and continuous deployment (CI/CD) pipelines to ensure seamless and automated code deployment to GCP environments. Implement and manage cloud monitoring and logging solutions using Dynatrace and GCP-native tools like Stackdriver (Monitoring, Logging, and Trace). Implement security best practices for cloud infrastructure, including identity and access management (IAM), encryption, and network security. Collaborate with development teams to design cloud-native applications that are optimized for performance, security, and scalability on GCP. Provide day-to-day support for development, QA, and production environments, ensuring availability and stability. Monitor and optimize cloud costs by analyzing resource utilization and recommending cost-saving measures such as right-sizing instances, using preemptible VMs, or implementing auto-scaling.