Staff Engineer, Compute

Datadog

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
—
Posted
24 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $214k
$151k most similar roles pay here $272k

This listing doesn't post a salary. Most similar roles pay $185,400–$243,400.

Based on 240 similar postings.

Employer

About Datadog

Datadog, Inc. is an American company that provides an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform.

Datadog currently has 266 open roles on FindRole.

Listed pay typically runs $161,000–$205,000 across 138 roles with salary data.

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At a glance

TL;DR · Staff Engineer, Compute

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Staff Engineer, Compute joins the Compute – Disruption and Workload Placement team to manage how a Kubernetes fleet scales for growing AI and cloud-native workloads. This role involves leading the technical direction of capacity management and workload placement across multiple cloud providers including AWS, Google Cloud, and Azure. The engineer will design and build systems to optimize how engineering workloads are scheduled and deployed while balancing reliability and performance. Day-to-day responsibilities include developing production software in Go to improve platform capabilities and automation, using data signals for forecasting, and influencing infrastructure architecture. The ideal candidate possesses significant experience with large-scale Kubernetes infrastructure, distributed cloud systems, and a strong systems mindset. They will solve complex problems regarding capacity orchestration and workload placement strategies to ensure engineering teams have the necessary compute resources at the right time.

What does a Engineer earn?

Median $185000 from 249 postings across 48 companies.

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Skills

Kubernetes Go AWS Azure Multi-cloud Capacity Management Cloud Infrastructure Automation Workload Placement

What you'll do

  • Lead the technical direction of capacity management for a Kubernetes platform across 100,000+ virtual machines.
  • Design and build systems to optimize workload scheduling and deployment across multiple cloud regions.
  • Develop production software in Go to improve Kubernetes capabilities and operational efficiency.
  • Manage multi-cloud capacity orchestration across AWS, Google Cloud, and Azure.
  • Use data signals to forecast growth and inform infrastructure decisions.
  • Improve workload placement strategies based on capacity constraints, reliability, and performance metrics.

What we're looking for

  • Significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems.
  • Experienced software engineer with strong programming skills in Go or a comparable systems programming language.
  • Hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).
  • Understanding of distributed cloud infrastructure.
  • Strong systems mindset for solving complex infrastructure, scheduling, or capacity management challenges.
  • Ability to work with operational data, capacity forecasting, and analytical approaches to inform engineering decisions.
  • Proven track record of providing technical leadership and influencing architecture across teams without direct management authority.

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