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.

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