Cognite - AI for Industry

Senior Director, Compensation & Benefits

USA (Phoenix) · Director

Sponsorship not specifiedDetected 6 days ago

Agentic AIComplianceM&ARecruitingHRISCompensationLeadership

About the role

If you view obstacles as signals to step forward - not backwards - you'll feel right at home here.
Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
This is a high-impact, business-critical role at the intersection of strategy, financial rigor, and employee experience.

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world's hardest, highest-impact problems.
With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
Strong collaborator and genuine partner across People & Organization, Finance, and the business - able to build trust quickly and lead through influence.
Partner closely with People Business Partners, Talent Acquisition, and Finance to ensure the rewards strategy is embedded in hiring, performance, and planning processes.
Collaborate across the People & Organization team as a genuine, hands-on partner - sharing knowledge, supporting others, and building the function's credibility through delivery.
You are a strategic thinker and operational executor - someone who can design the architecture and run the engine. You bring credibility at the Board level and the willingness to be in the detail when it matters.
How we reward, deploy, and develop our talent across these markets is central to our ambition.

Proven background in a high-growth technology or SaaS environment, including advisory experience at C-suite or Board level.
Experience designing and governing compensation frameworks across multiple geographies, including pay transparency and compliance requirements.
Experience supporting a company through IPO preparation, public-company transition, and/or M&A processes.
Familiarity with compensation benchmarking platforms such as Pave, Radford, or similar tools.
Experience designing compensation for technical, AI, and engineering talent markets.

Enhance and scale automated compensation processes leveraging platforms such as Pave, Radford, and Cognite's HRIS & Equity Management tool to ensure efficiency, accuracy, and governance.
Partner with Finance to align compensation planning with headcount budgets, financial forecasts, and organizational growth plans.
Ensure all compensation processes, records, and decisions meet the auditability and controls standards required for a pre-IPO company.
Define and track key Total Rewards KPIs, including market positioning, pay equity, compa-ratio distribution, retention impact, and incentive effectiveness.
Interpret workforce analytics to proactively inform compensation strategy, identify talent risk, and surface actionable insights for senior leadership and the Board.
Ensure compliance with global pay transparency regulations and leverage data across HRIS, Finance, and benchmarking platforms to maintain a clear, real-time picture of Cognite's total rewards competitiveness.

Define and maintain Cognite's global benefits philosophy, setting principles and guardrails that guide regional People Ops delivery and ensure a coherent total rewards experience globally.
Provide oversight of regional benefits programs, identifying gaps or misalignments with global strategy, and partnering with People Operations to address them.
We are seeking a Senior Director, Compensation & Benefits to serve as the global owner of Cognite's compensation philosophy, total rewards strategy, and operational governance.
You will report directly to, and partner closely with, the VP, People Operations & Rewards, while serving as the subject matter expert to the CHRO and CFO on compensation governance, equity, and global mobility.

This listing is sourced directly from Cognite - AI for Industry's careers page and normalized into a canonical job model.