Data Engineer - Capacity Planning - Apple Data Platform

Join Apple’s Data & AI infrastructure planning efforts by building the data pipelines, models, and analytical tools that turn infrastructure and financial signals into capacity planning insights. This onsite role in Austin, TX focuses on third-party cloud resources such as GPUs, TPUs, compute, and storage, helping teams understand utilization, forecast future demand, and support better infrastructure investment decisions.

What you’ll do

• Design and build pipelines and analytical foundations to measure current utilization, forecast future needs, identify capacity gaps, and improve infrastructure efficiency.
• Combine infrastructure telemetry, workload demand, capacity commitments, and financial data into trusted datasets and data products.
• Collaborate with engineering and business partners to translate complex infrastructure data into actionable insights for planning and investment.
• Work closely with Engineering, CIBO, Finance, and Procurement to support Apple’s infrastructure planning and decision-making.

What you bring

• 3+ years of experience in Data Engineering, Analytics Engineering, Infrastructure Analytics, or a related field.
• Strong SQL skills with experience working with large datasets.
• Experience with Python (or another language used for data processing and automation).
• Proven ability to build data pipelines, data models, and analytical datasets.
• Understanding of ETL/ELT patterns, data quality, and pipeline reliability.
• Experience using cloud billing and usage data from AWS, GCP, or Azure.
• 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 technical and non-technical partners.
• Bachelor’s degree in a related quantitative field (or equivalent practical experience).

Technologies you’ll use

SQL, Python, AWS, GCP, Azure

Preferred qualifications

• Experience with infrastructure capacity planning, forecasting, or resource-management data.
• Experience working with GPU, TPU, CPU, storage, or cloud infrastructure.
• Understanding of AI/ML infrastructure and accelerator utilization.
• Experience with infrastructure cost, billing, or utilization datasets.
• Experience with data-platform tools such as Spark, Trino, Airflow, Kafka, or similar technologies.
• Experience with Tableau or other visualization platforms.
• Familiarity with infrastructure economics, cloud commitments, or capacity optimization.
• Experience partnering with Engineering, Finance, and Procurement on infrastructure planning.