FinOps Program Manager

Responsibilities

• Maintains and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS.
• Builds and maintains forecasts for engineering spend, collaborating with Finance and engineering leaders.
• Collaborates with engineering, product, and TPMs to integrate cost considerations into roadmaps, architectural decisions, and execution plans.
• Led cost optimization initiatives, such as rightsizing, commitment strategies, and workload efficiency improvements.
• Creates and maintains dashboards and reporting that make spend understandable and actionable for both engineers and executives.
• Develops and implements FinOps practices and processes, including showback/chargeback models, unit economics, and cost ownership frameworks.
• Works with data and engineering teams to improve cost visibility, forecasting accuracy, and operational efficiency.
• Drives alignment and behavior change, helping teams balance cost, performance, reliability, and velocity through data-driven decision making.

Requirements

• 6–10+ years of relevant experience working at the intersection of engineering, infrastructure, data, or finance in a cloud-native or SaaS environment.
• Proven experience partnering closely with engineering teams to influence decisions involving cloud infrastructure, data platforms, AI/ML workloads, or SaaS spend.
• Experience managing AI and machine learning spend, including tracking usage costs, forecasting budgets, and identifying cost-optimization opportunities.
• Working understanding of modern cloud-native architectures, including core components such as compute, storage, networking, data pipelines, and managed services—enough to engage credibly with engineers on design, tradeoffs, and cost drivers.
• Strong foundation in cost analysis, forecasting, budgeting, and variance management, with the ability to translate data into clear, actionable insights.
• Comfort working directly with data, including writing SQL (or effectively using AI-assisted tools to do so) to explore datasets, validate assumptions, and answer ad hoc questions.
• Experience building clear, high-quality dashboards and BI artifacts that are not only accurate, but intuitive and delightful for engineers and leaders to use.
• Demonstrated success driving adoption and behavior change—embedding cost awareness into day-to-day engineering workflows, not just producing reports.
• Experience owning and delivering cross-functional programs end-to-end, often without direct authority or a dedicated team.
• Familiarity with FinOps principles and practices (e.g., shared ownership, showback/chargeback, unit economics, optimization strategies).
• Strong communication skills, with the ability to tailor complex technical and financial concepts for engineering, finance, and executive audiences.

Nice to Haves

• Hands-on familiarity with cloud cost management tools (e.g., AWS Cost Explorer, GCP Billing, Azure Cost Management, CloudHealth, Cloudability, or similar).
• Experience working with or supporting data platforms and AI/ML workloads, including understanding cost drivers for batch processing, streaming, storage, and model training/inference.
• Exposure to showback/chargeback models, cost allocation strategies, or product-level unit economics.
• Experience improving data models or pipelines that support analytics, reporting, or financial attribution.
• Familiarity with BI tools such as Mode, Tableau, Looker, or similar—and a strong eye for dashboard usability and design.
• Background in a technical role (e.g., engineering, TPM, infra, data, or engineering operations) before moving into a more cross-functional or business-oriented position.
• Experience operating in a high-growth or rapidly scaling environment, where cost structures and investment priorities are evolving quickly.