Google Kubernetes Engineer

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Job Summary:

We are seeking an experienced Google Kubernetes Engine (GKE) Engineer to join our team for a crucial platform migration project. The ideal candidate will be responsible for managing and optimizing Kubernetes clusters on Google Cloud Platform (GCP) to ensure seamless integration and performance of the cloud environment.

Key Responsibilities:

• Design, deploy, and manage Kubernetes clusters on Google Kubernetes Engine (GKE) to support the platform migration.
• Optimize GKE cluster performance and resource utilization, ensuring high availability and scalability.
• Collaborate with development and operations teams to integrate microservices, databases, and other components into the Kubernetes environment.
• Implement and maintain CI/CD pipelines for GKE deployments, including automated testing and continuous integration.
• Monitor cluster health, troubleshoot issues, and provide support for resolving GKE-related problems.
• Ensure security best practices are followed, including managing access controls, network policies, and secrets.
• Document deployment processes, cluster configurations, and operational procedures.

Qualifications:

• Proven experience with Google Kubernetes Engine (GKE) and Kubernetes in a production environment.
• Strong knowledge of containerization technologies, particularly Docker, and container orchestration with Kubernetes.
• Experience with cloud platforms, especially Google Cloud Platform (GCP).
• Proficiency in managing and automating deployments using Kubernetes manifests, Helm charts, or other tools.
• Familiarity with CI/CD tools and practices, particularly in the context of Kubernetes deployments.
• Solid understanding of networking, storage, and security concepts related to Kubernetes and cloud environments.
• Excellent problem-solving skills and the ability to work effectively in a collaborative team environment.

Preferred Skills:

• Experience with data storage solutions like S3 and integration with Kubernetes.
• Knowledge of Apache Airflow and its integration with Kubernetes.
• Familiarity with monitoring and logging tools, such as Prometheus, Grafana, and ELK Stack.
• Experience with Python or other scripting languages for automation tasks.