Cloud Cost Optimization Specialist

3 days ago

Anand, Gujarat, India beBeeAnalyst Full time ₹ 1,80,00,000 - ₹ 2,40,00,000

As a Business Intelligence Analyst, you will play a critical role in supporting our organization's strategic vision of expanding data entitlement.

Job Summary:

  • Analyze workflows and operational processes to identify optimization opportunities
  • Develop comprehensive metrics and dashboards for platform monitoring and decision-making
  • Support the Enterprise Data Council with data-driven insights for strategic direction and product management

Core Responsibilities:

  • Conduct data analysis and automation using SQL, Python, or R
  • Implement cloud cost optimization initiatives with focus on anomaly detection and cost avoidance strategies
  • Maintain sophisticated cost models and estimation frameworks for infrastructure services and resiliency capabilities
  • Support Reserved Instances (RI) and Savings Plans (SP) optimization to achieve annual 10% cost savings target

Infrastructure Operations & Resiliency Support:

  • Monitor platform utilization, performance metrics, and operational health across our services
  • Support L1/L2 operational activities for our Operations & Support Team
  • Assist with capacity planning, resource allocation, and infrastructure automation initiatives

Required Qualifications:

  • Bachelor's degree in Business Analytics, Data Science, Information Systems, or related technical field
  • 3-5 years of progressive experience in data analysis, business intelligence, and cloud operations
  • Advanced proficiency in SQL, Python, or R for complex data analysis and automation
  • Hands-on experience with AWS cloud platform and FinOps practices

Preferred Qualifications:

  • Direct experience with big data analytics platforms
  • Knowledge of cloud cost management tools and advanced FinOps methodologies
  • Experience with utilities or energy industry data and operations

Key Collaborations & Reporting:

  • Reports to Technology Leadership team
  • Works closely with Operations & Support, Platform Engineering, Data Engineering, and Architecture teams

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