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Salary: USD 165,500 - 289,600 / annual
ServiceNow is seeking a highly experienced Senior Staff Cloud FinOps Analyst to lead enterprise-scale cloud financial optimization across AWS, Microsoft Azure, Google Cloud Platform, private infrastructure, and emerging AI services.
This role operates at the intersection of Engineering, Finance, Product, Capacity Planning, Procurement, and cloud service providers. You will transform complex cloud Cost & Usage data into actionable strategies that improve infrastructure efficiency, unit economics, commitment performance, and gross margin.
Key responsibilities include:
**Governance and Accountability**: Work with Engineering, Finance, Product, and platform teams to establish clear ownership models and accountability structures. Partner with engineering teams to build automation behind ownership and accountability, including tagging and allocation enforcement, owner assignment, budget and threshold alerting, and cost-signal routing. Maintain the operating model for governance with documented standards, regular review cadence, and clear escalation paths. Track adherence to standards and close gaps where spend is unowned or misattributed.
**Rate Optimization**: Develop and continuously improve ServiceNow's multi-cloud rate optimization strategy. Manage Reserved Instances, Savings Plans, Committed Use Discounts, capacity reservations, and other provider-specific pricing instruments. Analyze consumption forecasts, contractual pricing, workload demand, coverage, utilization, expiration, break-even position, and stranded-commitment risk. Build scenarios quantifying expected savings, financial exposure, and forecast sensitivity. Partner with Finance, Procurement, Engineering, and cloud providers to execute and adjust commitment portfolios.
**Savings Realization**: Build and manage an enterprise optimization pipeline covering rate, usage, waste, architecture, and operational efficiency. Quantify opportunity, implementation complexity, risk, confidence, and expected value. Establish consistent methodologies for measuring identified, accepted, implemented, and realized savings. Validate results against actual billing and usage data. Create executive scorecards covering opportunity value, accountable ownership, implementation progress, realized savings, and residual risk.
**AI-Powered Cost & Usage Tooling**: Help shape ServiceNow's homegrown, AI-powered FinOps Control Tower. Work with Data Engineering, FinOps Engineering, Business Intelligence, and Product teams to define requirements, analytical models, semantic definitions, and practitioner experiences. Develop AI-assisted capabilities for anomaly detection, forecasting, variance explanations, commitment analysis, optimization recommendations, and natural-language exploration of Cost & Usage data. Help create conformed multi-cloud datasets and interactive applications for showback, optimization, planning, executive reporting, and unit economics.
**Cost Visibility and Leadership**: Develop allocation and unit-economic models and drive ownership visibility and financial accountability. Serve as a trusted advisor to senior Engineering, Finance, Product, and Infrastructure leaders. Influence technical decisions, lead complex cross-functional initiatives, mentor FinOps practitioners, and translate detailed analysis into clear executive recommendations.
**Requirements:**
- 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years experience; or equivalent experience
- Experience leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving (including using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact)
- Extensive FinOps, cloud economics, infrastructure analytics, or technology-finance experience
- Strong AWS, Azure, and GCP pricing knowledge
- Advanced SQL, forecasting, and financial-modeling skills
- Demonstrated expertise in rate optimization, rightsizing, savings validation, and cloud unit economics
- Experience building internal data products and applying AI to analytical workflows is strongly preferred
