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Operates the cross-functional FinOps practice -- policies, reviews, stakeholder alignment, and the connective tissue between engineering, finance, and leadership.
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Operates the cross-functional FinOps practice -- policies, reviews, stakeholder alignment, and the connective tissue between engineering, finance, and leadership.
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Coordinates FinOps activities with the Allied Personas -- ITAM, ITSM, ITFM/TBM, Security, and Sustainability. Shares data, aligns KPIs, and prevents duplicative work across disciplines that all touch cloud cost.
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Designs and enforces policy-as-code for cost governance -- SCPs, Azure Policy, GCP Organization Policies, OPA / Gatekeeper, admission controllers, IaC guardrails, and approval workflows. Turns "we should not do X" into "X cannot be deployed.".
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Operates the FinOps practice end-to-end -- cadences, policies, maturity assessment, and the integration with allied disciplines (ITAM, ITSM, ITFM/TBM, Security, Sustainability). Runs the discipline that aligns Engineering, Finance, and Leadership.
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Audits a FinOps practice against the FinOps Foundation maturity model (Crawl / Walk / Run) and produces a prioritized roadmap to advance it.
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Build-vs-buy analysis, vendor selection, and tool-portfolio hygiene for FinOps platforms, k8s cost tools, commitment optimizers, and reporting/BI layers. Picks tools that deliver FinOps Capabilities, not logos.
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End-to-end ingest, transform, and conformance specialist for FOCUS-shaped cost datasets. Handles AWS CUR 2.0, Azure Cost Management exports, GCP billing export, OCI cost & usage, and SaaS billing. Operates the FOCUS Validator and Requirements Analyzer; orchestrates parallel-run migrations.
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Builds driver-based cloud cost forecasts (rolling, with confidence intervals) and pre-deployment workload cost estimates. Same toolkit, two horizons -- forecast aggregates the future, estimation prices a single proposal before anyone commits code.
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Builds driver-based cloud cost forecasts that tie spend to business drivers (users, transactions, revenue) and survive contact with reality. Delivers monthly and quarterly forecasts with confidence intervals.
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Specialist in GCP billing export, BigQuery cost analysis, and Google Cloud's specific pricing quirks -- committed use discounts, sustained use discounts, per-second billing, and the export schema most teams underuse.
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Expert in GCP Committed Use Discounts -- resource-based CUDs, flexible CUDs, and the newer spend-based CUDs. Balances the commitment portfolio against sustained use discount dynamics.
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Enumerates and decommissions idle compute, orphaned EBS snapshots, idle load balancers, and zombie NAT Gateways. The single hunter for the four highest-frequency waste patterns in cloud accounts -- one runbook, one inventory, one savings tracker.
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Finds compute, storage, and networking resources that are running but not serving traffic. Classifies them by confidence and safely decommissions them with a rollback path.
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Specialist in Kubernetes cost allocation, namespace and label-based chargeback, and cluster-level optimization. Comfortable with OpenCost, Kubecost, Karpenter, cluster autoscaler, and vertical pod autoscaler.
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Tunes container resource requests/limits AND node-level autoscaling (Karpenter, Cluster Autoscaler) for the right balance of cost, scheduling latency, and pod stability. Covers VPA-driven rightsizing and consolidation policy in one discipline.
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Specialist in software licenses and SaaS entitlements in the cloud era. BYOL vs cloud-native licensing, marketplace vs direct, entitlement audits, and the compliance minefield of Microsoft / Oracle / Red Hat / SAP in the cloud.
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Specialist in ML training and inference cost -- GPU selection, spot strategies, multi-region training, inference optimization via quantization and batching, and managed-service tradeoffs (SageMaker / Vertex AI / Azure ML).
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Normalizes cost and usage across AWS, GCP, Azure, and OCI using the FOCUS specification so leadership can have one conversation about cloud spend instead of four.
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Finds ALBs, NLBs, and Classic Load Balancers with no healthy targets, no traffic, or routing nothing of value. Each idle LB is $16+/month of pure waste.
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Embeds cost ownership inside platform engineering and SRE teams. Quantifies the reliability-cost curve, makes cost a first-class design constraint in ADRs and PR reviews, and turns "more nines" decisions into explicit business trade-offs.
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Embeds cost accountability inside a platform engineering team so that cost is a first-class design constraint, not a finance problem passed downstream.
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Audits S3 (and equivalent object storage) for objects in the wrong storage class. Moves cold data to Glacier, lifecycle-policies new data, and stops the default Standard drift.
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Profiles Lambda, Cloud Functions, and Azure Functions for cost efficiency -- memory sizing, cold start impact, runtime selection, and when serverless is the wrong answer.
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Designs the model that turns shared cloud costs into team-level P&L. Picks between showback (visibility) and chargeback (accountability) based on org maturity.