Senior FinOps Analyst

SolarWinds•Austin, TX

About The Position

The Senior FinOps Analyst role is critical for optimizing cloud spending and driving financial accountability and cloud strategy across engineering and business units. This senior position requires a seasoned professional who can think strategically across multiple business units and cloud providers, with a focus on identifying and tracking high-impact savings initiatives. The role has expanded to include ownership of SaaS spend governance, AI/ML token and consumption cost management, and enterprise-wide cloud financial controls as the organization scales its use of cloud-native and AI-powered services.

Requirements

3-7 years working in a dedicated FinOps role at a SaaS company, with demonstrated experience spanning cloud infrastructure costs, SaaS spend management, and consumption-based AI/ML cost governance.
Deep understanding of cloud pricing models and cost management features of at least one major cloud provider (AWS, Azure, or GCP).
Proven ability to perform complex financial modeling, variance analysis, and business case development for optimization initiatives.
Deep understanding of cloud infrastructure and services of at least one major cloud provider (AWS, Azure, or GCP) and experience rightsizing containerized and non-containerized cloud workloads.
Hands-on experience building or maturing a SaaS spend management program, including license management, vendor contract governance, shadow IT controls, and chargeback frameworks.
Familiarity with token-based and consumption-based pricing for AI/ML services (e.g. OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI).
Experience building cost observability for LLM APIs, implementing budget guardrails, and partnering with engineering teams to optimize prompt efficiency and model selection.
Expertise with data analytics platforms (Power BI, Tableau), FinOps tools (e.g. CloudHealth, AWS CID, Azure FinOps toolkit), SaaS management platforms, and analysis tools (e.g. SQL, Azure Functions, AWS Athena).
Exceptional verbal and written communication skills with the ability to present complex subjects clearly and concisely.
Capable of presenting financial and strategic insights to senior leadership followed by actionable insights to more technical audiences (developers and engineers).
Bachelor degree in Finance, Information Technology, or a related field.

Nice To Haves

Familiarity with SaaS management platforms (e.g. Zylo, Torii, Flexera, Apptio) is strongly preferred.
Master of Business Administration is a plus.
FinOps Certified Practitioner, FinOps Certified Engineer, FinOps Certified FOCUS Analyst, and other cloud certifications are highly desirable.
Certifications or coursework related to AI/ML cost management or SaaS Operations are a plus.

Responsibilities

Own and maintain a standardized process, using data analytics and reporting tools, providing context on cloud spending to senior leadership and keeping internal teams informed about their cloud usage and costs.
Coordinate with finance, senior leadership, and directors to manage the cloud lifecycle and identify financial constraints for cloud strategy across all teams and cloud providers (AWS, Azure, GCP).
Proactively identify, prioritize, and drive execution on opportunities to reduce costs and increase the value of cloud investments.
Advise senior leadership on negotiating reseller agreements, track progress towards commitments, and ensure the organization’s cloud strategy is reflective of any obligations.
Engage with 3rd-parties offering service-specific discounts and coordinate with engineering teams to review and implement.
Coordinate with engineering contractors and their project managers to enforce cost constraints and include FinOps best practices in the statement of work.
Coordinate with Accounts Payable and FP&A to ensure cloud costs are correctly allocated and book chargebacks from shared services and bulk discounts.
Establish a FinOps program to promote best practices, define policies and standards (e.g. chargeback, tagging, resource deployments), and enforce cost visibility and accountability.
Define clear KPIs to monitor the realized financial results of completed cloud initiatives and the forecasted results of future initiatives.
Collaborate with directors and engineering teams to align optimizations with development initiatives to create a cloud strategy that delivers within financial constraints.
Manage the purchase of pre-ordered capacity for the organization (e.g. savings plans, reserved instances, pricing tiers) to balance savings with flexibility while avoiding waste.
Oversee and optimize the FinOps tool stack (e.g. Cloud Health, native cloud tools, and custom data analytics) to drive speed, accuracy, and quality of FinOps data and automation.
Build and maintain a comprehensive SaaS spend management program that provides full visibility into the organization's software subscriptions, licenses, and vendor contracts.
Maintain an authoritative inventory of all SaaS subscriptions and licenses across business units, identify redundant or underutilized tools, and work with procurement to rationalize the portfolio.
Partner with procurement and legal to negotiate SaaS agreements, enforce renewal governance, and identify consolidation opportunities that reduce total cost of ownership.
Establish chargeback/showback frameworks for SaaS costs by team, product, and cost center to drive accountability and align spend with business value.
Define and enforce SaaS procurement policies including approval workflows, acceptable-use standards, and shadow IT controls to prevent unauthorized spend.
Leverage SaaS management platforms (e.g. Zylo, Torii, Flexera, or Apptio) to track license utilization and adoption rates, flagging low-usage seats for rightsizing or elimination.
Own the financial governance of AI/ML inference costs, API consumption, and token-based pricing across all AI services used within the organization.
Develop dashboards and reporting pipelines that track token consumption and associated costs by team, product, model, and use case for LLM and AI API services (e.g. OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI).
Define token and API consumption budgets per team and product line, implement automated alerting for threshold breaches, and enforce guardrails to prevent runaway spend.
Collaborate with AI/ML and engineering teams to evaluate trade-offs between model capability and cost, recommending prompt optimization, caching strategies, model tiering, and batching to reduce per-unit token costs.
Establish governance frameworks for consumption-based and metered SaaS pricing models, ensuring contracts include appropriate usage caps, overage protections, and volume commitment structures.
Implement token-level cost allocation and chargeback/showback mechanisms so that AI costs are attributed accurately to the products and teams driving consumption.
Analyze consumption patterns to identify opportunities for provisioned throughput, committed use discounts, or pre-purchased capacity for AI services, balancing cost savings with throughput flexibility.