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Staff Engineer, Compute

Hybrid in Ireland·Added 2 months ago (last checked 26 Oct)

Datadog

26 open roles

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Our summary

Work mode: Hybrid, Ireland
Experience: Senior level

Skills

Nice to have

Requirements

What we're looking for

You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems.
You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language.
You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure.
You have a strong systems mindset and enjoy solving complex infrastructure, scheduling, or capacity management challenges.
You are comfortable working with operational data, capacity forecasting, or analytical approaches that inform engineering decisions.
You have a proven track record of providing technical leadership across teams and influencing architecture without relying on direct management authority.

Pay & benefits

What you'll get

Generous and competitive benefits package
New hire stock equity (RSUs) and employee stock purchase plan
Continuous career development and pathing opportunities
Employee-focused best in class onboarding
Internal mentor and cross-departmental buddy program
Friendly and inclusive workplace culture

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

The role

As a Staff Engineer on Datadog's Compute - Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth.

What you'll do

Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers.
Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance.
Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale.
Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency.
Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies.

How you'll work

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

Hiring process

4 steps3 interviewsa task to do

Initial screen
With a recruiter and/or hiring manager
A first conversation for the hiring team to get to know you and hear your aspirations.
Face-to-face interview
With hiring manager and team members
Conversations with the recruiter, hiring manager or team members; may consist of multiple rounds or panels depending on the role.
Take-home project
In your own time · Not every role
Some roles include a take-home project; the recruiter explains its scope and expectations.
Executive interview
With an executive leader · Not every role
For some roles, a final conversation with an executive leader about your experience and the wider team.
Selection and offer · With a recruiter

One of the steps is expected to happen in person; virtual rounds run on Zoom and travel is arranged by Datadog.
Certain engineering roles use AI-assisted coding interviews, announced in advance; AI is not allowed in other live coding rounds.
The recruiter shares next steps and timelines after each interview.

About Datadog

Industry: Observability
Founded: 2010
Employees: 5,000–10,000
Headquarters: New York City, USA

In their own words

About the company & team

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Additional information

Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your experience, we encourage you to apply.

Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog's Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

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