Solution Architect - Varicent

Cloudflare Cloudflare · Enterprise · Austin, TX, Toronto, ON · Accounting and Finance

Cloudflare is seeking a Solution Architect to join their Finance & Business Operations Organization, focusing on Global Commissions Tooling & Strategy. The role involves configuring Varicent compensation models, ensuring accurate and timely setup of incentive plans, and optimizing for scalability and usability. Responsibilities include end-to-end testing, performance analysis, risk assessment, documentation, and monitoring data flows. The ideal candidate will have strong SQL skills and experience with enterprise ICM tools.

What you'd actually do

  1. Develop and configure Varicent compensation models and calculation logic. Act as the primary technical builder for system enhancements, ensuring all plans are set up accurately and on time.
  2. Identify and implement best practice configurations and build techniques, optimizing for scalability and usability while ensuring solutions align with stakeholder needs.
  3. Plan and execute end-to-end testing (QA/UAT) for all system changes. You will be responsible for identifying bugs, validating fixes, and ensuring error-free deployments.
  4. Review and analyze application performance, to provide enhancement recommendations and process improvements.
  5. Provide risk assessment for new functionality and enhancements.

Skills

Required

  • 4+ years in Sales Compensation, Sales Operations, or Systems Administration
  • 3+ years of hands-on experience configuring Varicent (or a similar enterprise ICM tool like Anaplan/Xactly)
  • Firm grasp of end-to-end commission processes
  • Strong SQL skills
  • Analytical & Detailed

Nice to have

  • Experience with a SaaS business model.
  • Prior experience working in the SaaS, Cybersecurity, or Cloud Infrastructure space, with familiarity with usage-based or consumption-based compensation models.
  • Experience working with large-scale, complex datasets.

What the JD emphasized

  • primary technical builder
  • end-to-end testing
  • complex datasets is required
  • high attention to detail