Senior GTM Analytics Manager
About The Position
Cloudflare is hiring a Senior GTM Analytics Manager for its GTM Intelligence team. The team helps the go-to-market organization make faster, better decisions using trusted data, partnering with Sales, Technical Sales, Services, Finance, and central Data teams. This senior individual contributor will set and execute the vision for how information scales across technical customer-facing organizations, including Pre- and Post-Sales Operations, Solutions Engineering, Forward Deployed Engineering (FDE), and Professional Services. The role has wide influence and no direct reports. The position focuses on building the foundations for self-serve analytics rather than producing more dashboards or one-off analyses. The manager will develop single sources of truth, align metrics to actions, and establish data models, metric definitions, and context layers that enable executives, frontline managers, field engineers, and AI agents to get reliable answers. The role combines technical expertise and strategic partnership, including collaboration with Data Engineering and senior business stakeholders, and leadership on how analytics should evolve as AI increasingly answers business questions. Available locations are Austin, Texas; San Francisco, California; New York City; Atlanta, Georgia; or Denver, Colorado. The posting also lists a Colorado-remote compensation range. Compensation may vary by work location. The role is eligible for Cloudflare’s equity plan. Applicants who reach the offer stage may be asked to attend an in-person interview at a Cloudflare office or hub. The position may require access to information controlled under U.S. export laws; an offer may be conditioned on authorization to receive such technology without export-license sponsorship.
Requirements
- At least 8 years of experience in analytics, business intelligence, analytics engineering, or GTM/Services operations at a high-growth B2B SaaS or technology company.
- Direct experience supporting at least one of Pre- or Post-Sales Operations, Solutions/Sales Engineering, Forward Deployed Engineering, Professional Services, or Customer Success, with understanding of those teams' work, measures, and data.
- Deep data-modeling expertise, including dimensional modeling, entity design, and metric-layer design; able to review and challenge data models.
- Expert SQL skills and hands-on experience with modern data-stack tools such as BigQuery, dbt, or a semantic/metrics layer such as dbt Semantic Layer, LookML, or Cube.
- Strong working knowledge of GTM and services-system data, such as Salesforce, professional services automation tools, and product usage or telemetry data.
- Informed understanding of how AI changes analytics, including semantic layers, retrieval and context design for LLMs, text-to-SQL, agent-based access to governed data, and the data foundations needed for accuracy.
- Track record of defining and rolling out source-of-truth metrics across multiple stakeholder groups, including resolving disagreements over definitions.
- Proven ability to lead complex cross-functional programs without formal authority and influence executives and engineers.
- Excellent written and verbal communication skills, including translating ambiguous business questions into precise technical requirements and communicating technical concepts back to business stakeholders.
- BA/BS in a quantitative, technical, or business field.
Nice To Haves
- Master’s degree in Data Science, Analytics, Computer Science, or an MBA.
Responsibilities
- Define and drive a multi-year strategy, maturity model, and phased roadmap for how Pre-Sales, Post-Sales, Solutions Engineering, FDE, and Professional Services find, trust, and use data.
- Develop and communicate an approach to scaling information in an AI-first environment, including semantic layers, governed metrics, and context that enable AI assistants and agents to provide accurate, business-grounded answers.
- Review dashboards, reports, and tools across supported teams and plan consolidation, retirement of duplicates, and transition toward a single source of truth.
- Define, document, and implement official metrics for supported teams.
- Keep metric definitions aligned with corporate Finance and Data definitions and resolve disagreements with clear, defensible logic.
- Serve as the main business and technical partner to the central Data team for supported stakeholders.
- Influence and review data-model design across Salesforce, professional services tools, product usage and telemetry, support, and finance systems.
- Design how users obtain answers through self-serve access, natural-language and AI-assisted querying, embedded workflow insights, and curated metric catalogs.
- Establish a formal intake and governance process for metric and data requests, including prioritization, ownership, certification, and change management.
- Build trusted relationships with leaders in Sales, Solutions Engineering, FDE, Professional Services, Customer Success, Operations, Finance, and Data.
- Explain complex technical and analytical ideas clearly to executives to support decision-making.
Benefits
- Medical/Rx insurance
- Dental insurance
- Vision insurance
- Flexible Spending Accounts
- Commuter Spending Accounts
- Fertility and family-forming benefits
- On-demand mental health support and Employee Assistance Program
- Global Travel Medical Insurance
- Short- and long-term disability insurance
- Life and accident insurance
- 401(k) Retirement Savings Plan
- Employee Stock Participation Plan
- Flexible paid time off covering vacation and sick leave
- Leave programs, including parental, pregnancy health, medical, and bereavement leave
- Equity plan participation
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
