FinOps Engineer -B

Tata Consultancy Services; India; Sur place; INR 1 500 000 - 2 000 000; Plein temps

Résumé du poste

Tata Consultancy Services is seeking a FinOps Engineer to optimize and govern cloud spend across Azure and GCP. This role blends FinOps practice with data engineering to deliver cost analytics and actionable insights to engineering, finance, and operations teams.

You will build dashboards in Power BI, automate cost-collection processes, and advise on reservations and savings plans. The ideal candidate has hands-on experience with cloud billing, scripting for automation, and strong stakeholder

Qualifications

• Proven experience managing cloud costs in Azure and GCP.
• Strong understanding of FinOps principles and cloud financial management.
• Experience with chargeback/showback and cloud billing systems.
• Automation and scripting experience for cost optimization workflows.
• Excellent analytical and data interpretation skills.
• Strong stakeholder engagement and communication abilities.

Responsabilités

• Monitor, analyze, and optimize cloud spend across Azure and GCP.
• Implement and manage chargeback and showback processes for internal teams.
• Advise on and manage reservations and savings plans to improve cost efficiency.
• Design, build, and maintain Power BI reports and dashboards for cloud cost analytics.
• Automate data collection, processing, and reporting for cloud cost management.
• Collaborate with engineering, finance, and operations teams to drive cloud financial best practices.
• Identify cost-saving opportunities and lead their implementation.
• Stay current on pricing models, cost management tools, and FinOps best practices.

Connaissances

FinOps

Cloud cost management

Analytical skills

Stakeholder communication

Automation scripting

Data analysis

Outils

Power BI

pySpark

Microsoft Fabric

Shell/Bash

Description du poste

Role: FinOps Engineer

The FinOps Engineer is responsible for optimizing, managing, analyzing, and reporting cloud spend across Azure and GCP. This role combines FinOps practice with data engineering skills to build reliable cost analytics, automate cost optimization workflows, and deliver actionable insights to engineering, finance, and operations stakeholders. The person should be able to contribute immediately. This is not a learn-on-the-job assignment, and the required knowledge and experience will be validated in conversations.

Responsibilities:

• Monitor, analyze, and optimize cloud spend across Azure and GCP environments.
• Implement and manage chargeback and showback processes for internal teams and business units.
• Advise on and manage reservations and savings plans to improve cost efficiency.
• Design, build, and maintain Power BI reports and dashboards for cloud cost analytics.
• Automate data collection, processing, and reporting for cloud cost management.
• Work with cloud financial data, tagging, allocation, and cost governance processes.
• Collaborate with engineering, finance, and operations teams to drive cloud financial best practices.
• Identify cost‑saving opportunities and lead their implementation.
• Stay current on pricing models, cost management tools, and FinOps best practices.

Required Skills:

• Proven experience managing cloud costs in Azure and GCP.
• Strong understanding of FinOps principles and cloud financial management.
• Experience with chargeback/showback and cloud billing systems.
• Proficiency in Power BI or similar reporting/visualization tools.
• Automation and scripting experience for cost optimization workflows.
• Excellent analytical skills with the ability to interpret complex data sets.
• Strong communication skills for stakeholder engagement.
• Data engineering capability with Microsoft Fabric, Power BI, and pySpark.

Must Have:

• Data Engineering expertise.
• Microsoft Fabric.
• Power BI.
• pySpark.

Great to Have:

• FinOps knowledge and certification.
• Cloud infrastructure knowledge.
• FOCUS data schema experience.

Wanted:

• Python.
• Shell / Bash.
• Infrastructure-as-code principles for automating cost optimization workflows.