Role: Senior FinOps Program Lead
Experience: 10+ years
Key Responsibilities- FinOps Program Leadership
- Lead and manage enterprise FinOps programs across multi-cloud environments (AWS, Azure, Google Cloud Platform), ensuring alignment between engineering, finance, and business stakeholders.
- Define and execute FinOps roadmaps covering cost visibility, optimization, and governance maturity milestones.
- Drive executive-level reporting, cost reviews, and optimization planning sessions with senior client stakeholders.
- Own and enforce FinOps governance frameworks including tagging strategies, showback/chargeback models, and budget enforcement.
- Establish and track FinOps KPIs such as RI/SP coverage %, effective savings rate, unit cost, and utilization metrics.
- Stakeholder Engagement & Client Management
- Serve as the primary US-side point of contact for client leadership, ensuring visibility and confidence in delivery progress.
- Facilitate cross-functional alignment across engineering, finance, and executive leadership teams.
- Present cost savings opportunities, program updates, and ROI outcomes to senior and C-suite stakeholders.
- Translate complex cloud financial data into business-relevant insights and actionable recommendations.
- Cost Optimization & Automation
- Drive cloud cost optimization initiatives including Reserved Instance/Savings Plan procurement, rightsizing, idle resource cleanup, and workload scheduling.
- Collaborate with automation engineers to operationalize optimization levers at scale using Python-based pipelines and cloud APIs.
- Oversee integration and analysis of data from FinOps tools such as IBM Cloudability, AWS Cost Explorer, Azure Cost Management, and Google Cloud Platform Billing.
- Support development and maintenance of cost dashboards and reporting in Power BI or equivalent BI platforms.
- Identify and prioritize the highest-ROI optimization opportunities across business units and cost centers.
- AI-Forward Enablement
- Champion the integration of AI-forward tooling into FinOps workflows, including LLM-powered chatbots for cost queries, anomaly alerts, and self-service reporting.
- Collaborate with AI engineers to align agentic systems and RAG-based pipelines with FinOps use cases.
- Support the adoption of intelligent automation to reduce manual effort and accelerate decision-making cycles.
- Bring a growth mindset toward emerging AI tooling and help the client team build capability in this space.
Required Qualifications- 8 15 years of total experience, with at least 5+ years in enterprise FinOps, cloud financial management, or cloud cost optimization roles.
- Demonstrated experience leading FinOps programs for large enterprises or Fortune 500 clients across multi-cloud environments (AWS, Azure, and/or Google Cloud Platform).
- Deep understanding of FinOps principles: cost allocation, tagging governance, showback/chargeback, RI/SP optimization, anomaly detection, and KPI benchmarking.
- Strong stakeholder management skills with a track record of engaging senior business and technology leaders effectively.
- Experience with FinOps tooling such as IBM Cloudability, Cloud Health, AWS Cost Explorer, Azure Cost Management, or equivalent.
- Hands-on experience with cost reporting and dashboard delivery using Power BI, Tableau, or similar BI tools.
- Solid understanding of automation concepts and comfort collaborating with engineering teams on Python-based pipelines and cloud API integrations.
- Excellent communication, presentation, and executive reporting skills.
- US-based with ability to engage in client-facing interactions aligned to US business hours.
Preferred Qualifications- FinOps Certified Practitioner (FinOps Foundation) or equivalent cloud financial management certification.
- Experience working within a consulting or managed services delivery environment (Big 4, boutique advisory, or GSI).
- Exposure to AI-forward tools, including LLM-powered chatbots, agentic workflows, or natural language interfaces for cloud cost management.
- Familiarity with Python, SQL, or scripting languages sufficient to collaborate closely with automation engineers.
- Experience with Agile/Scrum delivery models in cross-functional, globally distributed teams.
- Background in enterprise governance, compliance, and policy enforcement in cloud environments.