GCP DevOps & Cloud Engineer

Job Description:

Responsibilities

• Architect, deploy, and maintain scalable data infrastructure in GCP with a focus on Cloud Composer (Airflow) and Google Kubernetes Engine (GKE).
• Manage containerized workloads using Docker and Kubernetes, including lifecycle management, networking, monitoring, and troubleshooting. Collaborate with data engineering teams to migrate traditional workloads to containerized platforms.
• Implement and maintain CI/CD pipelines using tools like Jenkins, Git, and Terraform
• Ensure observability and reliability of data pipelines and containerized services using Prometheus, Grafana, and other monitoring tools.
• Apply best practices for container security, image vulnerability scanning, and configuration management.
• Support both open-source and Google-native technologies that interact with Composer and GKE, such as CloudSQL, BigQuery, Pub/Sub, and Artifact Registry Support day to day platform operations

Required Qualifications

• 5+ years of experience with container orchestration platforms (Kubemetes, GKE, AKS, EKS).
• 5+ years of hands-on experience with Google Cloud Platform, including IAM, networking, and resource management.
• 5+ years of experience deploying and managing Docker containers in production environments.
• Strong understanding of Kubernetes architecture, including control plane components and networking.
• Experience with Python (5+ years), especially in the context of automation and data workflows.
• Experience with Composer (Airflow) DAG development and orchestration.
• Proficiency in Linux-based infrastructure and scripting languages (Bash, Python, Java and GoLang are a plus).
• Familiarity with container monitoring, logging, and troubleshooting tools.

Preferred Qualifications

• Experience with Helm, Terraform, and Jenkins for deployment automation.
• Exposure to SQL, NoSQL, and CloudSQL databases.
• Experience migrating legacy applications to containerized platforms.
• Knowledge of open-source data tools and Google Cloud services that support large-scale data environments.