Coupa

Coupa

Compensation Analyst - 11588

Canada

Sponsorship not specifiedCAD 68k-CAD 91kDetected 41 days ago
ExcelHRHRISCompensationCollaborationMicrosoft Office

About the role

  • Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers.
  • Learn more on Life at Coupa blog and hear from our employees about their experiences working at Coupa.

Requirements

  • We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins.
  • Advanced proficiency in Microsoft Excel, including: Pivot tables, VLOOKUP/XLOOKUP, IF/THEN logic

Nice to have

  • Bachelor's degree in Human Resources, Finance, Business, or related field
  • 2-5+ years of relevant compensation, HR analytics, or consulting experience
  • Self-starter mentality - able to work independently, take initiative, and navigate ambiguity
  • Proven ability to problem-solve and "figure things out" when answers are not immediately clear
  • Proficient in Microsoft Office Suite, including Word, PowerPoint, and Excel
  • Complex, nested formulas and data manipulation
  • Strong ability to work with and analyze large, complex datasets
  • Experience with HRIS systems (e.g., Dayforce) preferred

Compensation

  • Hands-on experience with salary surveys, preferably including Radford

Company info

  • At Coupa, we're at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend. 🔹
  • We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence. 🔹
  • Join a company where your work has a global, measurable impact on our clients, the business, and each other.

Equal opportunity

  • Coupa complies with relevant laws and regulations regarding equal opportunity and offers a welcoming and inclusive work environment.

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