Multi-Cloud FinOps Lead / Architect

Job Description – Multi-Cloud FinOps Lead / Architect

Experience: 12–15 years
Cloud Platforms: Azure, AWS and GCP
Role Focus: FinOps Strategy, Cloud Cost Optimization, Governance and Product Lifecycle Management

Job Location: Chennai / Bangalore

Job Mode: Remote

Notice: 0 - 30 Days

Key Responsibilities

• FinOps Strategy & Advisory: Define and drive enterprise-wide multi-cloud FinOps strategy, operating models, maturity assessments and transformation roadmaps. Act as a strategic advisor to leadership, Finance, product owners and engineering teams.
• FinOps Across Product Lifecycle: Embed FinOps practices throughout the product lifecycle—from product planning, architecture and development to testing, production deployment, operations, modernization and decommissioning. Establish cost-conscious engineering practices and governance checkpoints.
• Cloud Architecture & Cost Efficiency: Advise product and engineering teams on cost-efficient cloud architecture, technology selection, infrastructure sizing, scalability, resilience and performance trade-offs across Azure, AWS and GCP.
• Multi-Cloud Cost Management: Drive cloud cost visibility, allocation, budgeting, forecasting, anomaly detection and financial reporting across subscriptions, accounts, projects, applications and business units.
• Cost Optimization & Recommendation Analysis: Identify and evaluate optimization opportunities across compute, storage, databases, networking, containers and managed services using Azure Advisor, AWS Compute Optimizer, GCP Active Assist and other native or commercial tools.
• Pricing Analysis & Savings Validation: Analyze enterprise agreements, contracted discounts, actual and amortized costs, resource utilization and billing data. Recalculate provider-generated savings estimates using customer-specific pricing, validate financial benefits and track realized savings.
• Commitment & Commercial Optimization: Develop and manage optimization strategies for Azure Reservations and Savings Plans, AWS Reserved Instances and Savings Plans, and GCP Committed Use Discounts. Monitor coverage, utilization, expiry and the financial impact of infrastructure changes.
• FinOps Governance & Stakeholder Management: Establish FinOps governance frameworks, policies, KPIs, accountability models and review mechanisms. Collaborate with Finance, Engineering, Product Management, Cloud Operations and leadership to drive adoption and continuous improvement.
• FinOps Tooling, Analytics & Automation: Evaluate and implement FinOps platforms such as Apptio Cloudability, Flexera, Harness and Mavvrik. Drive automation of billing analysis, optimization tracking, dashboards and reporting using Excel, Power BI, SQL, Python and cloud-native APIs.
• Optimization Execution & Business Outcomes: Lead optimization initiatives from opportunity identification through technical assessment, stakeholder approval, implementation and financial validation. Drive measurable cost savings, improved unit economics, cost predictability and sustainable cloud financial accountability.

Requirements Required Qualifications & Skills

• 12–15 years of IT experience, including significant experience in cloud architecture, cloud operations, cloud financial management and FinOps.
• Strong hands-on expertise in at least two of Azure, AWS and GCP, with working knowledge of the third.
• Experience establishing enterprise FinOps strategies, governance frameworks and optimization programs.
• Strong understanding of cloud pricing, enterprise discounts, billing, commitment management and financial savings validation.
• Experience advising engineering and product teams on cloud architecture and cost optimization throughout the product lifecycle.
• Strong analytical, stakeholder management, consulting and executive communication skills.
• FinOps Foundation certification and relevant cloud architecture certifications preferred.

Interested peoples share your details and CV's mentioned mail id: [email protected]

Pay: ₹2,000,000.00 - ₹4,800,000.00 per year

Work Location: Remote