Senior / Staff FinOps Engineer / Architect, Apple Data Platform

The Apple Data Platform powers analytics, machine learning, and critical decision-making systems across Apple. As the scale of our data and compute grows, cost efficiency and fiscal stewardship are vital to maintaining Apple's culture of innovation and responsibility.

Description

We are seeking a Staff FinOps Engineer / Architect to design and drive the next generation of cost governance, efficiency, and optimization systems for Apple's Data Platform. You will lead architecture and development of frameworks that make cost, usage, and efficiency visible, actionable, and intelligent across Apple's large-scale data infrastructure.","responsibilities":"You will design and build the foundational FinOps architecture for the Apple 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 Apple's internal and cloud environments.

Partner with platform and infrastructure teams to integrate cost efficiency automation - 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 - identifying underutilized clusters, GPU idle time, and unoptimized workloads - and 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 Apple Cloud, AIML, and platform teams to ensure every dollar of compute delivers maximum value.

Preferred Qualifications

Experience in ML systems, GPU scheduling, or large-scale training/inference platforms.

Familiarity with AWS, GCP, or internal Apple infrastructure cost constructs.

Background in capacity planning, forecasting, or resource optimization for shared infrastructure.

Experience designing data models, metrics, and pipelines for cost telemetry.

Contributions to open-source FinOps or observability frameworks.

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience)

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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .