DE-Cloud FinOps Engineer-GDSN02

The opportunity

As a Senior FinOps Engineer in the Cloud Engineering team, you will deliver multi-cloud financial management solutions for global clients. The primary focus is core FinOps—cost visibility and allocation, budgeting and forecasting, anomaly management, workload and rate optimization, governance, chargeback/showback and business-value realization. Secondary skills include applying AI to improve FinOps operations, understanding token economics, and working with leading third-party FinOps platforms.

Your key responsibilities

• Own cloud cost visibility, data ingestion, normalization, tagging, allocation and reporting across Azure, AWS and GCP.
• Implement Showback and chargeback models, shared-cost allocation, account and subscription mapping, invoice reconciliation and cost-data quality controls.
• Develop budgets, forecasts, variance analysis, planning models, unit economics and executive dashboards aligned with business objectives.
• Drive anomaly detection and management, including thresholds, alerts, root-cause analysis, ownership, corrective actions and reporting.
• Deliver workload optimization through rightsizing, idle-resource elimination, scheduling, storage and network optimization, and architecture recommendations.
• Lead rate optimization covering reservations, savings plans, committed-use discounts, licensing, marketplace commitments and coverage/utilization tracking.
• Establish FinOps policies, governance forums, KPIs, maturity assessments, optimization backlogs and accountability across engineering, finance, procurement and product teams.
• Configure and operate native and third-party FinOps tools for data integration, allocation, budgeting, forecasting, anomaly management, optimization and workflow automation.
• As a secondary capability, apply AI for FinOps use cases such as natural-language cost analysis, predictive forecasting, anomaly triage and recommendation summarization, with appropriate human validation.
• Support token economics by measuring, allocating and optimizing AI consumption using metrics such as cost per token, request, application, user or business outcome.

Skills and attributes for success

• Strong knowledge of core FinOps capabilities: cost data ingestion, allocation, reporting and analytics, anomaly management, planning and estimating, forecasting, budgeting, benchmarking and unit economics.
• Hands-on expertise in workload optimization, rate optimization, licensing and SaaS cost management, invoicing, chargeback, policy and governance, and FinOps practice operations.
• Ability to translate cloud cost and usage data into actionable recommendations and measurable savings, cost avoidance, forecast accuracy and business-value outcomes.
• Practical experience with multi-cloud billing data, FOCUS or equivalent schemas, SQL, Python, APIs and business-intelligence tools.
• Hands-on knowledge of third-party FinOps tools such as IBM Apptio Cloudability, Flexera One, VMware CloudHealth, Kubecost, Harness CCM, CloudZero, Finout, Vantage or equivalent.
• Working knowledge of AI for FinOps use cases and the ability to validate AI-generated forecasts, anomalies and optimization recommendations.
• Basic knowledge of token economics, including token usage attribution, model pricing, cost-per-request and cost-per-business-outcome analysis.
• Strong stakeholder management across engineering, finance, procurement, product and leadership teams.

To qualify for the role, you must have

• BE/B.Tech/MCA or equivalent, with 3–7 years of relevant industry experience and demonstrable delivery experience in FinOps or cloud cost engineering.
• Strong hands-on knowledge of Azure, AWS or GCP infrastructure, billing constructs and native cost-management services; practical multi-cloud experience is preferred.
• Proven experience in cost allocation, Showback/chargeback, budgeting, forecasting, anomaly management, unit economics, workload optimization and rate optimization.
• Experience implementing or operating at least one third-party FinOps platform, including data onboarding, business mapping, dashboards, budgets, forecasts, optimization and governance workflows.
• Strong Python, SQL, REST API and cloud-native CLI skills, with experience building cost data pipelines, reports and auditable automation.
• Proficiency with Terraform or equivalent infrastructure-as-code tooling and integration with CI/CD and policy controls.
• Working knowledge of AI-powered FinOps capabilities such as forecasting, anomaly detection and recommendation generation is desirable but not mandatory.
• Awareness of token economics and AI consumption cost drivers is desirable.

Preferred Skills

• FinOps Certified Practitioner; FinOps Certified Professional, FinOps Certified Engineer or FOCUS certification is advantageous.
• Azure, AWS or Google Cloud architecture, cloud economics or FinOps-related certifications.
• Advanced experience with any of the 3rd party tool - IBM Apptio Cloudability, Flexera One, VMware CloudHealth, Kubecost, Harness CCM, CloudZero, Finout, Vantage or equivalent FinOps platforms.
• Knowledge of Kubernetes cost allocation, OpenCost, SaaS cost management, commitment automation and optimization workflow integration.
• Familiarity with AI for FinOps, token economics and cloud AI pricing models as secondary capabilities.

Your people responsibilities

• Foster teamwork and lead by example
• Participating in the organization-wide people initiatives
• Excellent written and oral communication skills; writing, publishing, and conference-level presentation skills a plus

Technologies and Tools

• Native cloud cost tools: Microsoft Cost Management, AWS Cost Explorer/CUR/Cost Optimization Hub, and GCP Cloud Billing.
• Enterprise FinOps platforms: IBM Apptio Cloudability, Flexera One, VMware CloudHealth and comparable multi-cloud cost-management solutions.
• Engineering-led and specialist FinOps tools: Kubecost/OpenCost, Harness CCM, CloudZero, Finout, Vantage, Spot by Flexera or equivalent.
• Data and analytics: FOCUS, SQL, Python, Power BI, Tableau/Looker, Fabric, BigQuery, Snowflake or equivalent.
• Automation and integration: GitHub/GitLab/Bitbucket, Azure DevOps or equivalent CI/CD, REST APIs, Terraform, Bicep/CloudFormation, ServiceNow and Jira.
• Cloud-native operations: Docker, Kubernetes, Prometheus, Grafana, Azure Monitor, Datadog, Splunk or equivalent observability tooling.
• Secondary AI exposure: AI-assisted forecasting, anomaly detection and cost analysis, plus token usage and model pricing telemetry.

What we look for

• A proven record of delivering core FinOps outcomes across visibility, allocation, budgeting, forecasting, anomaly management and optimization.
• Practical experience delivering measurable savings, cost avoidance, forecast accuracy, allocation coverage, commitment utilization and unit-cost improvement.
• Strong hands-on capability with cloud-native and third-party FinOps platforms, cost data, dashboards, integrations and automation.
• An engineering mindset that converts recommendations into governed, repeatable and auditable operational actions.
• Interest in AI for FinOps and token economics as complementary skills, without losing focus on foundational FinOps delivery.
• Strong collaboration, client communication and knowledge-sharing skills, with the abili