FinOps Specialist

Workday•Pleasanton, CA

2d•$89,800 - $159,600•Hybrid

About The Position

Workday is seeking a FinOps Specialist to join their FinOps organization, which focuses on engineering the future of cloud economics. This role involves managing cloud spend across Workday's multi-cloud ecosystem on AWS and GCP, utilizing a cutting-edge stack with agentic AI tools and machine learning models for planning, forecasting, and cost optimization. The FinOps Specialist will act as the link between technical capabilities and financial objectives, re-engineering cloud-native operations to drive efficiency, developing metrics for ML-driven forecasting, and designing frameworks for AI tools. The position requires a high-potential professional to provide subject matter expertise for enterprise-wide initiatives, transforming cloud data into operational excellence.

Requirements

3+ years' experience defining, designing, and implementing solutions to achieve a desired business outcome by evaluating, diagnosing, and evolving existing business processes and software technologies, and by applying metrics for evaluating economic success in the public cloud.
1+ year of experience analyzing or operating software systems in one of the public cloud service providers (AWS, GCP, or Azure)
Bachelor's degree or equivalent work experience
Outstanding written, visual representation, and verbal communication skills.
Strong ability to establish relationships, influence without authority, and drive alignment across teams with varied strengths and leadership levels.
Outstanding organizational, interpersonal, and negotiation skills; flexible and adaptable; able to work in ambiguous situations.
Passion to serve our stakeholders and a commitment to delivering high-quality results.
Proficient in data analysis and planning and modeling tools, dbt, Lightdash, Adaptive Planning, Google Sheets and Excel.

Nice To Haves

Six Sigma certification is highly desirable.

Responsibilities

Diagnose and re-engineer cloud-native operations across AWS and GCP to drive efficiency improvements.
Develop sophisticated metrics that feed ML-driven forecasting models.
Design procedural frameworks that allow agentic AI tools to operate at scale.
Provide subject matter expertise to enterprise-wide initiatives.
Transform raw cloud data into operational excellence.