Apple is seeking a Senior Data Engineer to join the AI/ML team in Cupertino, California, United States. In this on-site role, you will design, build, and maintain scalable data pipelines, data platforms, and data integration solutions that enable reliable analytics, machine learning, and business intelligence across the organization. You will collaborate with machine learning researchers, engineers, and data scientists to power the Apple Foundation Model lifecycle and develop transformative products used by billions of users worldwide. Key qualifications include a bachelor’s or master’s degree in computer science, engineering, or a related field; 5+ years of experience in data engineering or distributed systems; strong Python skills; experience with ETL/ELT, event-driven architectures, and large-scale batch and streaming pipelines using technologies such as Pub/Sub, Dataflow (Apache Beam), and Spark (Dataproc). Deep expertise in Google Cloud Platform data ecosystem (BigQuery, Dataflow, Pub/Sub, Composer) and in data modeling, partitioning, clustering, and query optimization at scale. Familiarity with data governance, ML pipelines and MLOps workflows, and Generative AI workflows is a plus.

Apple is seeking a Senior Data Engineer to join the AI/ML team in Cupertino, California, United States. In this on-site role, you will design, build, and maintain scalable data pipelines, data platforms, and data integration solutions that enable reliable analytics, machine learning, and business intelligence across the organization. You will collaborate with machine learning researchers, engineers, and data scientists to power the Apple Foundation Model lifecycle and develop transformative products used by billions of users worldwide. Key qualifications include a bachelor’s or master’s degree in computer science, engineering, or a related field; 5+ years of experience in data engineering or distributed systems; strong Python skills; experience with ETL/ELT, event-driven architectures, and large-scale batch and streaming pipelines using technologies such as Pub/Sub, Dataflow (Apache Beam), and Spark (Dataproc). Deep expertise in Google Cloud Platform data ecosystem (BigQuery, Dataflow, Pub/Sub, Composer) and in data modeling, partitioning, clustering, and query optimization at scale. Familiarity with data governance, ML pipelines and MLOps workflows, and Generative AI workflows is a plus.