FinOps Analyst

About the role

JFrog is the global leader in software supply chain technology, delivering an end-to-end platform that provides complete visibility, security, and control for automating trusted software releases. We empower organizations to build and release software faster and more securely, fueling innovation without compromise. With a global footprint serving over 7,500 customers, including many Fortune 100 companies, we are actively shaping the future of software delivery. We are currently seeking an Analytics Engineer

Cloud & FinOps to spearhead data-driven decision-making across our cloud infrastructure and platform operations. This position is central to our ability to understand and optimize the complex relationship between our platform's operations and financial outcomes. The role focuses on constructing analytical solutions that provide deep visibility into cloud expenditures, infrastructure efficiency, and platform engagement patterns. You will architect data pipelines, build analytical models, and generate automated insights that connect our cloud billing data, infrastructure telemetry, and core business metrics. You will work in close collaboration with Cloud Platform Engineering, SRE, and Product teams to ensure a clear understanding of how infrastructure behavior and engineering choices directly influence our cloud spend and operational efficiency. Given our large-scale, multi-cloud environment, the role involves navigating significant data volumes to uncover the drivers of cost and system performance. A key component of this position involves leveraging modern, AI-driven analytics tools and models to enhance our data processing, pattern detection, and decision support capabilities. Experience with such technologies is a significant asset.

Key facts

What you'll do

You will design and own intake workflows that collect cloud billing exports, infrastructure telemetry, and diverse product metrics for the purpose of unified analysis. You will automate build processes for scalable analytics datasets that expose unit economics, capacity planning trends, and infrastructure utilization patterns. Establishing review routines will be essential to ensuring ongoing data accuracy, consistency, and governance across all analytical models and transformation logic. Your insights will directly guide engineering and leadership decisions as you ship clear recommendations focused on cost drivers and platform efficiency. You will forge strong partnerships with Cloud Platform, SRE, and Product teams to ensure our analytics remain aligned with evolving business objectives and operational needs. Investigating cost anomalies will involve a deep correlation of infrastructure usage, system behavior, and business activity to surface meaningful improvement opportunities. You will develop analytical frameworks that link operational metrics, business activity, and cloud spend to create robust unit economics and allocation models. Using AI-assisted tools to accelerate data exploration, pattern detection, and insight generation across our multi-cloud landscape will be a standard practice. You will translate complex datasets into clear, actionable insights and recommendations tailored for both engineering and leadership audiences. You will contribute to the creation of reusable data structures that promote efficiency and clarity in how cloud performance is measured and discussed across the organization.

Requirements

Demonstrated experience analyzing cloud cost and usage data across multiple providers to identify trends and optimization paths. Proven ability to develop analytical frameworks connecting infrastructure usage, operational metrics, and business activity. A track record of supporting FinOps initiatives by clarifying the impact of platform workloads and engineering choices on cloud spending. Experience investigating anomalies in cloud costs and infrastructure changes to find root causes and improvement options. Skill in designing and maintaining data pipelines that ingest billing exports, telemetry, metrics, and internal systems. Expertise in building analytics datasets and models optimized for cost analysis and infrastructure performance. A commitment to ensuring accuracy and consistency in analytical datasets through strong governance practices. The capability to analyze large datasets to uncover relationships among system behavior, utilization patterns, and cost outcomes. Experience creating frameworks for cost allocation, capacity planning, and performance monitoring. Excellent skill in translating complex datasets into clear insights and recommendations for technical and executive audiences. Hands-on experience with modern AI-assisted analytics tools to speed up exploration and investigation.

Nice to have

Experience working in large-scale multi-cloud environments generating substantial infrastructure and operational data.

Practical notes

Engagement: Full-time.

Location: Bangalore.