Data Engineer - Capacity Planning

DataJobs; Cupertino (CA); On-site; USD 129,000 - 225,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Apple employee stock programs

Expense reimbursement for education

Relocation assistance

Product discounts

Job summary

Apple is seeking a Data Engineer for Capacity Planning in Cupertino, CA (onsite) to design trusted datasets and analytical tooling that support forecasting of infrastructure demand and cost. The role begins with third-party cloud infrastructure capacity and planning, with the scope expected to expand to Apple-owned infrastructure over time.

You will build and maintain data pipelines and data models that capture infrastructure capacity, utilization, performance, and cost, feeding unit economics

Qualifications

• 3+ years in Data Engineering, Analytics Engineering, Infrastructure Analytics, or related field.
• Strong SQL skills with large datasets.
• Experience using Python or another language 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 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.
• Bachelor’s degree in CS/Engineering/Data Science/Stats/etc. or equivalent practical experience.

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 resources.
• Create cost models to compute unit economics such as cost per GPU hour, per job, and per 1M tokens.
• Combine workload demand, utilization telemetry, capacity commitments, and financial data into a shared planning framework.
• Reconcile model outputs to actual results and apply data-quality controls for missing tags, anomalies, and duplicates.
• Build forecasting and scenario-analysis tools to evaluate capacity, utilization, and pricing decisions ahead of infrastructure investment.
• Identify optimization opportunities including idle reserved capacity, underutilized clusters, and inefficient workloads, and quantify potential savings.
• Automate recurring capacity-planning, forecasting, and reporting workflows.
• Partner with engineering teams to understand workload growth, migrations, SLOs, and architecture changes that impact capacity needs.
• Work with CIBO, Finance, and Procurement to support cloud commitments and long-range capacity planning.
• Communicate insights, risks, and recommendations clearly to technical and business stakeholders.

Skills

SQL

Python

Data pipelines

Data modeling

ETL/ELT

Cloud billing data

Financial data reconciliation

AI/ML cost awareness

Analytical thinking

Stakeholder communication

Education

Bachelor's degree or equivalent in a quantitative field

Tools

Spark

Trino

Airflow

Kafka

Tableau

AWS

GCP

Azure

Job description

Apple is seeking a Data Engineer for Capacity Planning in Cupertino, CA (onsite) to design trusted datasets and analytical tooling that support forecasting of infrastructure demand and cost. The role begins with third-party cloud infrastructure capacity and planning, with the scope expected to expand to Apple-owned infrastructure over time.

Role Overview

You will build and maintain data pipelines and data models that capture infrastructure capacity, utilization, performance, and cost. The outputs will feed unit economics and forecasting tools to help leaders evaluate capacity, utilization, and pricing considerations before committing spend.

Key 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.
• Create cost models to compute unit economics such as cost per GPU hour, cost per job, and cost per 1M tokens based on measured production utilization.
• Combine workload demand, utilization telemetry, capacity commitments, and financial data into a shared planning framework.
• Reconcile model outputs to actual results and apply data-quality controls for missing tags, anomalies, and duplicate records.
• Build forecasting and scenario-analysis tools to evaluate capacity, utilization, and pricing decisions ahead of infrastructure investment.
• Identify optimization opportunities including idle reserved capacity, underutilized clusters, and inefficient workloads, and quantify potential savings.
• Automate recurring capacity-planning, forecasting, and reporting workflows.
• Partner with engineering teams to understand workload growth, migrations, SLOs, and architecture changes that impact 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.

Required 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 using Python or another language 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.

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.

Technologies

• SQL
• Python
• ETL/ELT
• AWS
• GCP
• Azure
• Spark
• Trino
• Airflow
• Kafka
• Tableau

Location

Cupertino, CA (onsite)

Compensation

USD 129,300 - 225,300 per year

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments, as well as relocation
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
• Discretionary restricted stock unit awards
• Ability to purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan
• Eligibility requirements and other terms of the applicable plan or program