Staff Engineer, Compute - Kubernetes Capacity & Multi-Cloud

United States Digital Space LLC; Dublin; Hybrid; EUR 120,000 - 170,000; Full time

Benefits offered by this job

RSUs

Career development

Onboarding

Mentor program

Inclusive culture

Job summary

Datadog is seeking a Staff Engineer on the Compute – Disruption and Workload Placement team to define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads across AWS, Google Cloud, and Azure.

You will shape capacity orchestration, influence platform architecture, and develop production Go services to improve scheduling, deployment, and operational efficiency while delivering reliable capacity across regions.

Qualifications

• Significant experience designing and operating large-scale Kubernetes-based infrastructure or platforms.
• Strong programming skills, ideally in Go or similar systems language.
• Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure).
• Proven ability to lead technically across teams and influence architecture.

Responsibilities

• Lead the technical direction of capacity management and workload placement for the Kubernetes platform spanning 100,000+ VMs across multiple clouds.
• Design and build systems to optimize scheduling and deployment across regions while balancing capacity, reliability, and performance.
• Partner with infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as the company scales.
• Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency.
• Use data and capacity signals to influence infrastructure decisions and forecasting.

Skills

Kubernetes

Go programming

Distributed systems

Cloud platforms (AWS/GCP/Azure)

Job description

Datadog is seeking a Staff Engineer on the Compute – Disruption and Workload Placement team to define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads across AWS, Google Cloud, and Azure.

You will shape capacity orchestration, influence platform architecture, and develop production Go services to improve scheduling, deployment, and operational efficiency while delivering reliable capacity across regions.