Cloud Engineer ( Google Cloud Engineer)

Job Summary

We are seeking a skilled and proactiveGCP Cloud Engineerwith strong expertise inGoogle Kubernetes Engine (GKE)andGoogle Cloud Dataproc. The ideal candidate will be responsible for designing, implementing, and managing cloud infrastructure and data processing pipelines on Google Cloud Platform. This role will support scalable deployment of applications and big data workflows, ensuring high availability, security, and performance.

Key Responsibilities

• Design, deploy, and manage containerized applications usingGoogle Kubernetes Engine (GKE).
• Implement and optimizeDataproc clustersfor batch and stream data processing.
• Develop and maintainCI/CD pipelinesfor container-based workloads.
• Collaborate with development and data engineering teams to design scalable, cloud-native solutions.
• Monitor and troubleshoot cloud infrastructure, ensuring high availability and reliability.
• Automate infrastructure provisioning using tools likeTerraform,Deployment Manager, orAnsible.
• Ensure security and compliance standards are met across all GCP environments.
• Optimize performance and cost-efficiency of cloud resources.
• Participate in incident response and root cause analysis.

Requirements

Required Skills and Qualifications

• Hands-on experience in cloud engineering with GCP.
• Strong experience withGKE(setup, maintenance, monitoring, scaling).
• Proficiency inGoogle Cloud Dataproc, including Spark and Hadoop job management.
• Solid understanding ofKubernetes concepts, Helm, and container orchestration.
• Familiarity withCI/CD tools(e.g., Jenkins, GitLab CI/CD, Cloud Build).
• Scripting and automation skills inPython,Shell, or similar.
• Experience withInfrastructure as Code (IaC)tools like Terraform.
• Strong knowledge of cloud networking, IAM, monitoring (Stackdriver/Cloud Monitoring), and logging.

Preferred Qualifications

• GCP Professional Cloud Architect or GCP DevOps Engineer certification.
• Experience with other GCP services like BigQuery, Cloud Functions, Pub/Sub, etc.
• Background in data engineering or DevOps practices.