What are the responsibilities and job description for the Senior FinOps Program Lead position at Calabitek?
Role: Senior FinOps Program Lead
location: Remote
Duration: 12 Months contract
location: Remote
Duration: 12 Months contract
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, CloudHealth, 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.
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, CloudHealth, 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.