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Apple

Data Engineer - Capacity Planning - Apple Data Platform

Cupertino, CA$129,300 – $225,300Posted 21 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

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3.1/5 in supportive management
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65% would recommend this company to other women
66% say the CEO supports gender diversity

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Help us build the data foundation for capacity planning across Apple's data and AI infrastructure. The Apple Data Platform organization is looking for a Data Engineer to build data pipelines, models, and analytical tools that help us understand infrastructure demand, utilization, capacity, and cost. The role will initially focus on third-party cloud infrastructure including GPUs, TPUs, compute, and storage and will expand over time to Apple-owned infrastructure. You will work closely with engineering, CIBO, Finance, and Procurement to help Apple make better infrastructure planning and investment decisions.

Description

As a Data Engineer focused on Capacity Planning, you will bring together infrastructure telemetry, workload demand, capacity commitments, and financial data into trusted datasets and data products. You will build the pipelines and analytical foundations used to understand current utilization, forecast future needs, identify capacity gaps, and improve infrastructure efficiency. You will partner with engineering and business teams to turn complex infrastructure data into actionable insights.","responsibilities":"Build and maintain data pipelines for infrastructure capacity, utilization, performance, and cost data.

Develop trusted data models for GPU, TPU, CPU, storage, and other infrastructure resources.

Build cost models that calculate unit economics such as cost per GPU hour, cost per job, and cost per 1M tokens using measured production utilization.

Integrate workload demand, utilization telemetry, capacity commitments, and financial data into a common planning framework.

Reconcile model outputs to actuals and implement data-quality controls for missing tags, anomalies, and duplicate records.

Build forecasting and scenario-analysis tools that help leaders evaluate capacity, utilization, and pricing decisions before committing spend.

Identify optimization opportunities such as idle reserved capacity, underutilized clusters, and inefficient workloads, and quantify the associated savings.

Automate recurring capacity-planning, forecasting, and reporting workflows.

Partner with engineering teams to understand workload growth, migrations, SLOs, and architecture changes that affect capacity needs.

Work with CIBO, Finance, and Procurement to support cloud commitments, infrastructure investment decisions, and long-range capacity planning.

Communicate insights, risks, and recommendations clearly to technical and business stakeholders.

Preferred Qualifications

Experience with infrastructure capacity planning, forecasting, or resource-management data.

Experience working with GPU, TPU, CPU, storage, or cloud infrastructure.

Experience with AWS, GCP, or similar cloud platforms.

Understanding of AI/ML infrastructure and accelerator utilization.

Experience with infrastructure cost, billing, or utilization datasets.

Experience with technologies such as Spark, Trino, Airflow, Kafka, or similar data-platform tools.

Experience with Tableau or other visualization platforms.

Familiarity with infrastructure economics, cloud commitments, or capacity optimization.

Experience partnering with Engineering, Finance, or Procurement on infrastructure planning.

Minimum Qualifications

3+ years of experience in Data Engineering, Analytics Engineering, Infrastructure Analytics, or a related field.

Strong SQL skills and experience working with large datasets.

Experience with Python or another language used for data processing and automation.

Experience building data pipelines, data models, and analytical datasets.

Understanding of ETL/ELT patterns, data quality, and pipeline reliability.

Experience working with cloud billing and usage data from AWS, GCP or Azure

Proven ability to build data models that reconcile to a financial source of truth

Understanding of AI and ML inference workloads and how model serving drives compute cost

Strong analytical and problem-solving skills.

Ability to work effectively with both technical and non-technical partners.

Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, Economics, Finance, or a related quantitative field, or equivalent practical experience.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $129,300 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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