Datadog

Datadog

People Strategy, Engineering

New York, New York, USA

Sponsorship not specified$162k-$216kDetected 8 hours ago
DatadogAccessibilityLeadershipCollaboration

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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About the role

  • We don't expect every box checked on day one.
  • If you're excited about the challenge and want to grow into it, we want to hear from you.
  • Datadog values people from all walks of life.

Responsibilities

  • Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles.
  • Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures.
  • Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices.
  • Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role.
  • Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business.
  • Operate in ambiguity and influence without formal authority, building trust with senior stakeholders even before the answer is clear.
  • You build consensus, challenge constructively and stay credible across differing perspectives.
  • This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people.
  • how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles.
  • You'll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale.

Requirements

  • You are equally comfortable setting direction and getting into the detail, able to move from strategy to execution without handing work off prematurely.
  • You are data-fluent, pragmatic and outcome-focused, with a strong bias towards delivery and follow-through.

Compensation

  • $162,000 - $216,000 USD

Benefits

  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Free, global mental health benefits for employees and dependents age 6+
  • Competitive global benefits
  • Datadog offers a competitive salary and equity package, and may include variable compensation.
  • Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes.
  • You have designed and delivered talent programs in a fast-growing, global organization, and partnered directly with executives on strategic people questions.
  • Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Company info

  • It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers.
  • 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.

Equal opportunity

  • Equal Opportunity at Datadog:
  • This form is for accommodation requests only and cannot be used to inquire about the status of applications.

Visa & Work Authorization

  • t 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

This listing is sourced directly from Datadog's careers page and normalized into a canonical job model.