## About the Role

JFrog is hiring an Analytics Engineer – Cloud & FinOps to improve visibility into cloud costs, infrastructure utilization, and platform usage. The role exists to turn cloud billing data, infrastructure telemetry, operational metrics, and business data into analysis that supports better engineering and leadership decisions.

You will work closely with Cloud Platform Engineering, SRE, and Product teams in a large-scale multi-cloud environment that generates significant volumes of infrastructure and operational data. The focus is on understanding how workload behavior and engineering choices affect cloud spend and operational efficiency. This position is based in Bangalore (Bellandur) and follows a mandatory three-days-in-office hybrid model.

## Key Responsibilities

– Analyze cloud cost and usage data across multiple cloud providers to identify cost drivers, trends, anomalies, and optimization opportunities.
– Build analytical frameworks that connect infrastructure usage, operational metrics, business activity, and cloud spend.
– Design and maintain data pipelines and transformations for cloud billing exports, infrastructure telemetry, operational metrics, and internal product and business systems.
– Develop scalable datasets and data models for infrastructure and cost analysis.
– Ensure analytical datasets remain accurate, consistent, and governed.
– Investigate cost anomalies and infrastructure changes to determine root causes and improvement opportunities.
– Support FinOps work, including cost allocation, unit economics, infrastructure utilization analysis, capacity planning, and operational performance monitoring.
– Translate complex findings into clear recommendations for engineering and leadership teams.
– Use AI-assisted tools and automated workflows to speed up data exploration, pattern detection, and insight generation.

## Required Skills

– Experience with modern data platforms such as Redshift, BigQuery, or Snowflake.
– Experience with analytics and visualization tools such as Tableau, Looker, Power BI, or QuickSight.
– Strong SQL and data modeling skills.
– Python for data analysis and automation.
– Experience working with large-scale operational or infrastructure datasets.
– Experience using AI-assisted development tools such as Cursor, Claude, Copilot, or similar.
– Strong analytical thinking and problem-solving ability.
– Ability to turn complex infrastructure data into clear, actionable insights.
– Comfort working in a cross-functional engineering environment.

## Preferred Skills

– Experience with cloud infrastructure data from AWS, Azure, or GCP.
– Familiarity with cloud billing datasets and cost management analytics.
– Experience analyzing large-scale infrastructure or telemetry data.
– Background in FinOps, cloud operations, platform engineering, or infrastructure analytics.
– Familiarity with Kubernetes or distributed systems environments.
– Experience with modern AI-driven analytics tools and models, including LLM-based analysis, automated insight generation, and intelligent data exploration.

## Cloud Platforms & Technologies

– **Cloud Providers:** AWS, Azure, GCP
– **Data Platforms / Warehouses:** Redshift, BigQuery, Snowflake
– **BI / Visualization:** Tableau, Looker, Power BI, QuickSight
– **Programming Languages:** SQL, Python
– **AI / Analytics:** LLM-based analysis, automated insight generation, intelligent data exploration
– **AI-Assisted Development Tools:** Cursor, Claude, Copilot
– **Infrastructure / Environments:** multi-cloud, Kubernetes, distributed systems

## FinOps Responsibilities

– Improve visibility into cloud spend and the drivers behind it.
– Identify cloud cost trends, anomalies, and optimization opportunities.
– Support cloud cost allocation and unit economics analysis.
– Contribute to capacity planning and infrastructure utilization analysis.
– Link infrastructure behavior and engineering decisions to cloud spend and operational efficiency.
– Build automated workflows that surface cost anomalies, usage trends, and system behavior changes.

## Why You Might Be Interested

This role offers the chance to work on large-scale multi-cloud data where infrastructure, cost, and business metrics are closely connected. It may suit candidates who want to combine analytics engineering with FinOps and operational decision support. The position also involves collaboration with Cloud Platform Engineering, SRE, and Product teams, so the work has direct impact across the organization. Candidates interested in AI-assisted analysis and cloud cost visibility may find the scope especially relevant.