Kubernetes Engineer

Req ID: 383118 

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Kubernetes Engineer (hybrid position in either Irving, TX or Charlotte, NC) to join our team in Dallas, Texas (US-TX), United States (US).

 * Please note, This is a hybrid position. The client’s main locations are in Irving, TX and Charlotte, NC. We are looking for someone who is nearby one of these locations to be able to go onsite for client support 2-3 days a week, and working remotely the other time.  Please be mindful of applying if you are not in an ideal commutable distance of one of these locations. 

About this Role:

We are seeking a Lead Infrastructure Engineer to help design, automate, and operate our next‑generation hybrid cloud and Kubernetes platforms. This role is ideal for an engineer who thrives on solving infrastructure challenges with automation and enjoys building reusable, self‑service capabilities that improve platform reliability and developer experience.

In this hands‑on role, you will contribute to the development of scalable infrastructure patterns, modernize compute from VMs to containers, and enable GitOps‑driven delivery across environments. You will partner closely with platform, security, and application engineering teams to build solutions that are secure, consistent, and easy for developers to consume.

This is a technical leadership position focused on engineering excellence, reusable patterns, and the evolution of our Kubernetes‑centered platform ecosystem.

Key Responsibilities

Platform Engineering & Architecture Contribution

• Build and maintain Kubernetes platforms, including cluster operations, add‑ons, curated Helm charts, and deployment standards.
• Develop reusable infrastructure modules and templates using Terraform, Ansible, or similar IaC tools.
• Support hybrid cloud infrastructure (Azure or GCP) following established architectural guidelines.
• Contribute to workload migration initiatives from virtual machines to containerized environments.
• Implement declarative, API‑driven infrastructure patterns aligned with GitOps workflows.

Operational Excellence

• Automate provisioning, configuration, and platform lifecycle tasks to reduce manual operations and improve stability.
• Leverage observability tooling (Prometheus, Grafana, logs, tracing) to improve performance monitoring and incident response.