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JFrog Logo JFrog · IT - Software Development

Senior Analytics Engineer – Cloud & FinOps

India, Bangalore · Job Posted March 26, 2026
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Job Description

JFrog is seeking a Senior Analytics Engineer – Cloud & FinOps to help drive data-driven decision making across our cloud infrastructure and platform operations. This role will focus on building analytics solutions that provide visibility into cloud costs, infrastructure utilization, and platform usage patterns. The engineer will develop data pipelines, analytical models, and automated insights that connect cloud billing data, infrastructure telemetry, and business metrics. Working closely with Cloud Platform Engineering, SRE, and Product teams, this role will help the organization better understand how infrastructure usage and engineering decisions impact cloud spend and operational efficiency. Our platform operates in a large-scale multi-cloud environment, generating significant volumes of infrastructure and operational data. The ideal candidate enjoys working with complex datasets and building analytical systems that help engineering teams understand cost drivers, infrastructure behavior, and system efficiency. In addition, the role is expected to leverage modern AI-driven analytics tools and models (e.g., LLM-based analysis, automated insight generation, and intelligent data exploration) to enhance data processing, pattern detection, and decision support capabilities. Experience working with such tools is highly valued.

Job Responsibility

  • Analyze cloud cost and usage data across multiple cloud providers to identify cost drivers, trends, and optimization opportunities
  • Develop analytical frameworks that connect infrastructure usage, operational metrics, and business activity
  • Support FinOps initiatives by improving visibility into how platform workloads and engineering decisions influence cloud spend
  • Investigate cloud cost anomalies and infrastructure changes to identify root causes and improvement opportunities
  • Design and maintain data pipelines and transformations that ingest data from sources such as: cloud billing exports
  • infrastructure telemetry
  • operational metrics
  • internal product and business systems
  • Build scalable analytics datasets and data models optimized for infrastructure and cost analysis
  • Ensure data accuracy, consistency, and governance across analytical datasets
  • Analyze large datasets to identify relationships between system behavior, infrastructure utilization, and cloud cost patterns
  • Develop analytical frameworks supporting: cloud cost allocation and unit economics
  • infrastructure utilization analysis
  • capacity planning
  • operational performance monitoring
  • Translate complex datasets into clear insights and recommendations for engineering and leadership teams
  • Leverage modern AI-assisted tools to accelerate data exploration, analysis, and investigation
  • Build automated workflows that help teams identify cost anomalies, usage trends, and system behavior changes more efficiently

Requirements

  • Strong SQL and data modeling expertise
  • Python for data analysis and automation
  • Experience building data pipelines and ETL/ELT workflows
  • Strong analytical thinking and problem-solving skills
  • Experience working with large-scale operational or infrastructure dataset
  • Experience using AI-assisted development tools such as Cursor, Claude, Copilot, or similar
  • Experience working with modern data platforms such as: Redshift, BigQuery, Snowflake
  • Experience with analytics and visualization tools such as: Tableau / Looker / Power BI / QuickSight
  • Experience working with cloud infrastructure data (AWS, Azure, or GCP)
  • Familiarity with cloud billing datasets and cost management analytics
  • Experience analyzing large-scale infrastructure or telemetry data
  • Experience working in FinOps, cloud operations, platform engineering, or infrastructure analytics environments
  • Familiarity with Kubernetes or distributed systems environments
  • Strong analytical and problem-solving abilities
  • Ability to translate complex infrastructure data into clear and actionable insights
  • Comfortable working in cross-functional engineering environment
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