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Ford Motor Company
Chennai, India
(on-site)
Posted
13 days ago
Ford Motor Company
Chennai, India
(on-site)
Job Type
Full-Time
Job Function
Engineering
Cloud Platform Engineering Manager
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Cloud Platform Engineering Manager
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
Job DescriptionWe are seeking a highly skilled and passionate GKE Platform Engineering Manager to join our growing team. This role is ideal for someone with deep experience in managing Google Kubernetes Engine (GKE) platforms at scale, particularly with enterprise-level workloads on Google Cloud Platform (GCP). As part of a dynamic team, you will design, develop, and optimize Kubernetes-based solutions, using tools like GitHub Actions, ACM, KCC, and workload identity to provide high-quality platform services to developers. You will drive CI/CD pipelines across multiple lifecycle stages, manage GKE environments at scale, and enhance the developer experience on the platform.
You should have a strong mindset for developer experience, focused on creating reliable, scalable, and efficient infrastructure to support developer needs. This is a fast-paced environment where collaboration across teams is key to delivering impactful results.
Responsibilities
- GKE Platform Management at Scale: Manage and optimize large-scale GKE environments in a multi-cloud and hybrid-cloud context, ensuring the platform is highly available, scalable, and secure.
- CI/CD Pipeline Development: Build and maintain CI/CD pipelines using tools like GitHub Actions to automate deployment workflows across the GKE platform. Ensure smooth integration and delivery of services throughout their lifecycle.
- Enterprise GKE Management: Leverage advanced features of GKE such as ACM (Anthos Config Management) and KCC (Kubernetes Cluster Config) to manage GKE clusters efficiently at the enterprise scale.
- Workload Identity & Security: Implement workload identity and security best practices to ensure secure access and management of GKE workloads.
- Custom Operators & Controllers: Develop custom operators and controllers for GKE, automating the deployment and management of custom services to enhance the developer experience on the platform.
- Developer Experience Focus: Maintain a developer-first mindset to create an intuitive, reliable, and easy-to-use platform for developers. Collaborate with development teams to ensure seamless integration with the GKE platform.
- GKE Deployment Pipelines: Provide guidelines and best practices for GKE deployment pipelines, leveraging tools like Kustomize and Helm to manage and deploy GKE configurations effectively. Ensure pipelines are optimized for scalability, security, and repeatability.
- Zero Trust Model: Ensure GKE clusters operate effectively within a Zero Trust security model. Maintain a strong understanding of the principles of Zero Trust security, including identity and access management, network segmentation, and workload authentication.
- Ingress Patterns: Design and manage multi-cluster and multi-regional ingress patterns to ensure seamless traffic management and high availability across geographically distributed Kubernetes clusters.
- Deep Troubleshooting & Support: Provide deep troubleshooting knowledge and support to help developers pinpoint issues across the GKE platform, focusing on debugging complex Kubernetes issues, application failures, and performance bottlenecks. Utilize diagnostic tools and debugging techniques to resolve critical platform-related issues.
- Observability & Logging Tools: Implement and maintain observability across GKE clusters, using monitoring, logging, and alerting tools like Prometheus, Dynatrace, and Splunk. Ensure proper logging and metrics are in place to enable developers to effectively monitor and diagnose issues within their applications.
- Platform Automation & Integration: Automate platform management tasks, such as scaling, upgrading, and patching, using tools like Terraform, Helm, and GKE APIs.
- Continuous Improvement & Learning: Stay up-to-date with the latest trends and advancements in Kubernetes, GKE, and Google Cloud services to continuously improve platform capabilities.
Qualifications
Experience:
- 8+ years of overall experience in cloud platform engineering, infrastructure management, and enterprise-scale operations.
- 5+ years of hands-on experience with Google Cloud Platform (GCP), including designing, deploying, and managing cloud infrastructure and services.
- 5+ years of experience specifically with Google Kubernetes Engine (GKE), managing large-scale, production-grade clusters in enterprise environments.
- Experience with deploying, scaling, and maintaining GKE clusters in production environments.
- Hands-on experience with CI/CD practices and automation tools like GitHub Actions.
- Proven track record of building and managing GKE platforms in a fast-paced, dynamic environment.
- Experience developing custom Kubernetes operators and controllers for managing complex workloads.
- Deep Troubleshooting Knowledge: Strong ability to troubleshoot complex platform issues, with expertise in diagnosing problems across the entire GKE stack.
Technical Skills:
Must Have:
- Google Cloud Platform (GCP): Extensive hands-on experience with GCP, particularly Kubernetes Engine (GKE), Cloud Storage, Cloud Pub/Sub, Cloud Logging, and Cloud Monitoring.
- Kubernetes (GKE) at Scale: Expertise in managing large-scale GKE clusters, including security configurations, networking, and workload management.
- CI/CD Automation: Strong experience with CI/CD pipeline automation tools, particularly GitHub Actions, for building, testing, and deploying applications.
- Kubernetes Operators & Controllers: Ability to develop custom Kubernetes operators and controllers to automate and manage applications on GKE.
- Workload Identity & Security: Solid understanding of Kubernetes workload identity and access management (IAM) best practices, including integration with GCP Identity and Google Cloud IAM.
- Anthos & ACM: Hands-on experience with Anthos Config Management (ACM) and Kubernetes Cluster Config (KCC) to manage and govern GKE clusters and workloads at scale.
- Infrastructure as Code (IaC): Experience with tools like Terraform to manage GKE infrastructure and cloud resources.
- Helm & Kustomize: Experience in using Helm and Kustomize for packaging, deploying, and managing Kubernetes resources efficiently. Ability to create reusable and scalable Kubernetes deployment templates.
- Observability & Logging Tools: Experience with observability tools such as Prometheus, Dynatrace, and Splunk to monitor and log GKE performance, providing developers with actionable insights for troubleshooting.
Nice to Have:
- Zero Trust Security Model: Strong understanding of implementing and maintaining security in a Zero Trust model for GKE, including workload authentication, identity management, and network security.
- Ingress Patterns: Experience with designing and managing multi-cluster and multi-regional ingress in Kubernetes to ensure fault tolerance, traffic management, and high availability.
- Familiarity with Open Policy Agent (OPA) for policy enforcement in Kubernetes environments.
Education & Certification:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Relevant GCP certifications, such as Google Cloud Certified Professional Cloud Architect or Google Cloud Certified Professional Cloud Developer.
Soft Skills:
- Collaboration: Strong ability to work with cross-functional teams to ensure platform solutions meet development and operational needs.
- Problem-Solving: Excellent problem-solving skills with a focus on troubleshooting and performance optimization.
- Communication: Strong written and verbal communication skills, able to communicate effectively with both technical and non-technical teams.
- Initiative & Ownership: Ability to take ownership of platform projects, driving them from conception to deployment with minimal supervision.
- Adaptability: Willingness to learn new technologies and adjust to evolving business needs.
Job ID: 79788921
Please refer to the company's website or job descriptions to learn more about them.
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