FinOps Consultant Job at Excelon Solutions, Sunnyvale, CA

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  • Excelon Solutions
  • Sunnyvale, CA

Job Description

Location - SCV/Austin onsite role

Responsibilities

You will design and build the foundational FinOps architecture for a large-scale Data Platform — the systems that enable cost visibility, efficiency, and accountability across thousands of workloads.

In this role, you will:

  • Lead the design of a scalable cost attribution and chargeback framework spanning compute, storage, caching, GPU, and network layers.
  • Build instrumentation and data pipelines that collect usage telemetry, normalize cost data, and surface insights across both internal and cloud environments.
  • Partner with platform and infrastructure teams to integrate cost efficiency automation — including autoscaling, throttling, resource reclamation, and policy enforcement.
  • Develop dashboards and reporting systems that provide real-time visibility into utilization, waste, and savings opportunities.
  • Guide efficiency initiatives across teams by identifying underutilized clusters, GPU idle time, and unoptimized workloads to drive measurable cost reduction.
  • Collaborate with Finance, Capacity Planning, and Engineering to define budgeting models, KPIs, and showback/chargeback policies.
  • Mentor engineers across the organization in FinOps best practices and foster a culture of fiscal accountability within engineering.

This is a high-impact, cross-functional role. You’ll work across cloud, AIML, and platform teams to ensure every dollar of compute delivers maximum value.

Minimum Qualifications

  • 8+ years of experience in software, infrastructure, or platform engineering with a focus on performance, scalability, or cost optimization.
  • Deep technical understanding of cloud and on-prem compute, storage, GPU/accelerator, and network cost models.
  • Proven experience building cost attribution, chargeback, or FinOps automation systems at scale.
  • Strong programming proficiency in Python, Go, or Java, and familiarity with large data systems (Spark, Kubernetes, or distributed schedulers).
  • Hands-on experience with observability platforms, telemetry collection, and usage analytics (e.g., Prometheus, Grafana, Datadog, or custom metrics pipelines).
  • Ability to model resource usage, design allocation frameworks, and build automation that enforces efficiency policies.
  • Strong collaboration and communication skills to influence partner engineering, finance, and capacity planning teams.
  • Comfort with ambiguity and proven ability to define structure and frameworks in new domains.
  • A passion for driving measurable cost and efficiency improvements through engineering excellence.

Job Tags

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