Senior GTM Analytics Manager

Responsibilities

• Define and drive a multi-year strategy for how Pre-Sales, Post-Sales, Solutions Engineering, FDE, and Professional Services find, trust, and use data, including a maturity model and a phased roadmap.
• Act as a thought leader on scaling information in an AI-first world, working out how semantic layers, governed metrics, and well-built context let AI assistants and agents give accurate, consistent answers grounded in our business.
• Review the current mix of dashboards, reports, and tools across these teams. Create a plan to consolidate them, retire duplicates, and move toward a single source of truth.
• Define, document, and carry out the official metrics for the teams you support.
• Keep metric definitions aligned with corporate definitions from Finance and Data, and resolve conflicts between teams with clear, defensible logic.
• Act as the main business and technical partner to the central Data team for the stakeholders you support.
• Influence and review the design of data models across systems such as Salesforce, professional services tools, product usage and telemetry, support, and finance.
• Design how people get answers: self-serve access, natural-language and AI-assisted querying, embedded insights in daily workflows, and curated metric catalogs.
• Set up a formal intake and governance process for new 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.

Requirements

• 8+ years 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 the following: Pre- or Post-Sales Operations, Solutions/Sales Engineering, Forward Deployed Engineering, Professional Services, or Customer Success. You understand how these teams work, how they're measured, and how their data is created.
• Deep data modeling expertise, including dimensional modeling, entity design, and metric layer design. You can review and challenge a data model, not just consume one.
• Expert SQL skills and hands-on experience with modern data stack tools such as BigQuery, dbt, or a semantic/metrics layer (for example dbt Semantic Layer, LookML, or Cube).
• Strong working knowledge of GTM and services systems data, such as Salesforce, professional services automation tools, and product usage or telemetry data.
• A clear, informed view on how AI changes analytics, including semantic layers, retrieval and context design for LLMs, text-to-SQL, and agent-based access to governed data, plus the data foundations those need to be accurate.
• A track record of defining and rolling out source-of-truth metrics across multiple stakeholder groups, including handling disagreements over definitions.
• Proven ability to lead complex, cross-functional programs without formal authority, and to influence executives and engineers alike.
• Excellent written and verbal communication skills, including turning ambiguous business questions into precise technical requirements and back again.

Preferred

• BA/BS in a quantitative, technical, or business field. A Master's in Data Science, Analytics, Computer Science, or an MBA is a plus.
• 8+ years 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 the following: Pre- or Post-Sales Operations, Solutions/Sales Engineering, Forward Deployed Engineering, Professional Services, or Customer Success. You understand how these teams work, how they're measured, and how their data is created.
• Deep data modeling expertise, including dimensional modeling, entity design, and metric layer design. You can review and challenge a data model, not just consume one.
• Expert SQL skills and hands-on experience with modern data stack tools such as BigQuery, dbt, or a semantic/metrics layer (for example dbt Semantic Layer, LookML, or Cube).
• Strong working knowledge of GTM and services systems data, such as Salesforce, professional services automation tools, and product usage or telemetry data.
• A clear, informed view on how AI changes analytics, including semantic layers, retrieval and context design for LLMs, text-to-SQL, and agent-based access to governed data, plus the data foundations those need to be accurate.
• A track record of defining and rolling out source-of-truth metrics across multiple stakeholder groups, including handling disagreements over definitions.
• Proven ability to lead complex, cross-functional programs without formal authority, and to influence executives and engineers alike.
• Excellent written and verbal communication skills, including turning ambiguous business questions into precise technical requirements and back again.

Benefits

• Equity This role is eligible to participate in Cloudflare’s equity plan.
• Health & Welfare Benefits
• - Medical/Rx Insurance
• - Dental Insurance
• - Vision Insurance
• - Flexible Spending Accounts
• - Commuter Spending Accounts
• - Fertility & Family Forming Benefits
• - On-demand mental health support and Employee Assistance Program
• - Global Travel Medical Insurance