GTM Data Specialist, Consumption & Revenue OperationsActive$138K–$190K

The opportunity

Cloudflare is changing how it grows and how it measures growth and Revenue and Consumption is becoming a core Go-To-Market (GTM) metric that shapes our GTM motions.

What you'll do

  • Design, model, and land targets: Build and evolve our target setting model, and own the methodology. Back-test them, land them with GTM leaders, and keep improving them.

  • Execute the strategy: Take direction from the Strategy Lead and turn it into working methods and recommendations, and flag early when the data says the plan should change.

  • Build scorecards: Work with our DIA and GTM Analytics teams to build and maintain scorecards with cross-functional partners covering field performance, data quality, and disputes.

  • Protect data integrity: Validate actuals, baselines, targets, revenue attribution, and account ownership against source systems such as BigQuery, and tie GTM Revenue back to Finance and Billing.

  • Support the field and apply the Rules of Engagement: Answer field questions and cases on baselines, quotas, crediting, and ownership, applying the Rules of Engagement consistently and keeping a record of each decision. Spot where a rule needs to change, and provide the account hierarchy and ownership data teams need to collaborate across geos on our most critical customers.

  • Support territory planning and partner across teams: Provide analytics to Geo Ops and central territory design so they can deliver successful territory and coverage plans with equitable distribution of opportunity and targets. Work with Finance, Billing, data engineering, IT, RevOps, and Compensation to define data needs and move manual spreadsheet work into governed data products.

What they're looking for

  • Use AI to scale the work: Use AI tools, to write and review SQL, speed up reconciliations, draft answers to common field questions, and automate recurring checks. Review every result for accuracy and follow Cloudflare policy on confidential data.