Senior Data Engineer: AI-Powered Music Ops Analytics

Apple Inc.; Cupertino (CA); On-site; USD 176,000 - 312,000; Full time

Benefits offered by this job

Health insurance

Stock options

Job summary

Apple Inc. in Cupertino, California, is seeking a Senior Data Engineer to architect and deploy AI-ready data pipelines that support Music Services Operations Analytics & Strategy.

You will help build scalable, modular systems spanning Music, Video, and Books, with reliable SLAs for internal teams, data scientists, and partners. The role emphasizes collaboration with data scientists and engineers to deliver high-performance datasets, advance analytics, and robust CI/CD maturity across the

Qualifications

• 7+ years of experience owning production data systems at massive scale.
• Advanced Python and SQL with Spark-based data processing.
• CI/CD pipelines and automated deployment workflows.
• Data quality management and anomaly detection capabilities.
• Strong cross-functional leadership and communication skills.
• Bachelor's degree in CS, Data Eng, or related field.

Responsibilities

• Build and scale data infrastructure with modular pipelines for massive scale.
• Champion AI and innovation; explore LLMs, RAG pipelines.
• Drive data quality and observability with validation and lineage.
• Enable advanced analytics with high-performance datasets and SLAs.
• Collaborate across Analytics, Operations, Engineering, and Partners.
• Lead self-service analytics and enforce CI/CD practices.

Skills

Python

SQL

PySpark

CI/CD

Data quality

Leadership

Communication

Problem solving

Education

Bachelor's degree in CS or related field

Tools

Apache Iceberg

Delta Lake

Spark

Tableau

Job description

Apple Inc. in Cupertino, California, is seeking a Senior Data Engineer to architect and deploy AI-ready data pipelines that support Music Services Operations Analytics & Strategy.

You will help build scalable, modular systems spanning Music, Video, and Books, with reliable SLAs for internal teams, data scientists, and partners. The role emphasizes collaboration with data scientists and engineers to deliver high-performance datasets, advance analytics, and robust CI/CD maturity across the