Kubernetes Global Topic Lead (GTL)

At NTT DATA Business Solutions, we drive innovation – from advisory and implementation to managed services and beyond, powered by a global team of over 18,500 experts representing over 90 nations in more than 30 countries. With SAP at our core and a powerful ecosystem of partners like Microsoft and ServiceNow, we continuously improve solutions and AI-driven technology to make them work for companies – and for their people.

We are part of NTT DATA, a $30+ billion business and technology services, AI and digital infrastructure leader. As a Global Top Employer, NTT DATA serves 75% of the Fortune Global 100 and, with experts in over 70 countries, co-innovates solutions that encourage experimentation and recognize great work.

With us, you have endless opportunities to think big, act bold and take ownership.

Make this the place where you belong, learn, and build your network

Make this the place where you grow

What makes us special:

Team-oriented corporate culture, collaboration as equals and steady knowledge transfer

Diversity & Inclusion (e.g. various initiatives & communities)

Flexible working hours, (e.g. hybrid working)

Inhouse Academy with a variety of professional technical training, soft skills training, SAP Learning Hub and certification opportunities

Company health benefits (e.g. Health Insurance, Optical, Dental and Medical checkup benefits)

Do you love challenges

We are seeking a Kubernetes Global Topic Lead (GTL) to design, build, operate, and continuously improve enterprise Kubernetes platforms supporting both traditional application workloads and emerging AI/GPU-based workloads. The ideal candidate will possess strong Linux, containerization, networking, and Kubernetes administration skills, with hands-on experience operating managed Kubernetes services, particularly Azure Kubernetes Service (AKS).

This role will be responsible for platform reliability, automation, security, observability, CI/CD integration, and supporting development teams consuming Kubernetes services at scale.

Reporting / Organization

• Reporting to Global Service Area Manager – Compute & Virtualization

Responsibilities

• Strong experience with Docker containers and Linux administration.
• Solid understanding of DNS, networking, ports/protocols, and load balancing.
• Hands-on experience managing Kubernetes clusters, workloads, storage, networking, security, and operations.
• Experience integrating Kubernetes with CI/CD and GitOps processes.
• Knowledge of monitoring, observability, performance tuning, and troubleshooting.
• Experience with Rancher for Kubernetes management.
• Strong preference for AKS and EKS experience; GKE experience is also valuable.
• Understanding of container image management, vulnerability scanning, and workload security.
• Basic knowledge of supporting GPU-enabled AI/ML workloads in Kubernetes environments.

Preferred: Longhorn, Cilium, Kube-VIP, Fleet, Harbor, and Zabbix.

Education/Experience/Skills

• 3–7+ years of experience in Infrastructure, Cloud, Platform Engineering, DevOps, or Site Reliability Engineering (SRE) roles.
• 2–5+ years of hands-on experience administering and operating production Kubernetes environments.
• Experience deploying and supporting containerized applications using Docker and Kubernetes.
• Strong experience administering Linux-based systems and troubleshooting via command line.
• Experience with managed Kubernetes platforms, preferably:
• Azure Kubernetes Service (AKS), Amazon EKS (strong preference)
• Google GKE (Good to have)
• Experience with Kubernetes networking, storage, security, RBAC, secrets management, and cluster operations.
• Experience integrating Kubernetes platforms with CI/CD pipelines, GitOps workflows, and automation tools.
• Experience monitoring and troubleshooting production environments using observability and logging tools.
• Experience working in enterprise environments with multiple teams including infrastructure, security, networking, and application development.
• Exposure to Kubernetes-based AI/ML workloads and GPU-enabled clusters is advantageous.
• Strong communication skills with the ability to explain design choices and trade-offs to both technical and non-technical stakeholders.
• Collaborative working style, comfortable facilitating cross team discussions and design workshops.
• Self-driven and structured individual