Data Engineer - AIML Evaluation

As a Data Engineer on the Experimentation Platform team, you will take end-to-end ownership of the data infrastructure that drives experimentation across Apple. From architecting robust pipelines and data models to delivering dashboards and data-driven features, your work will directly shape how Apple teams measure, iterate, and innovate. This role blends autonomous, heads-down engineering with meaningful cross-functional collaboration. You will partner closely with teams across Apple — gathering requirements, supporting experiment execution, and signing off on delivered solutions together. We are looking for someone who treats data as a product: someone who is as thoughtful about the teams consuming their work as the systems producing it. Design, build, and maintain scalable data pipelines to support A/B experimentation workflows across Apple teams. Architect and manage data models and database schemas that enable complex analytical queries and statistical reporting. Develop data-driven features and statistical insights that enhance the capabilities of the experimentation platform. Build and maintain dashboards and data visualizations to surface experimentation metrics and operational health. Engage directly with internal customers to gather requirements, support experiment execution, and validate delivered solutions. Ensure data quality, reliability, and observability across all analytics pipelines and platform systems. Contribute to a collaborative team environment, balancing independent project ownership with close partnership across the analytics and platform teams. Master's degree in Computer Science, Data Engineering, or a related field, or equivalent experience. 4+ years of professional experience in data engineering or a closely related role. Strong proficiency in Python and advanced SQL. Solid understanding of data modeling, database schema design, and data warehousing concepts. Experience with large-scale distributed data processing and pipeline using frameworks such as Apache Spark. Experience with workflow orchestration tools such as Apache Airflow. Experience with deploying and managing CI/CD pipelines. Experience building data visualizations using tools such as Apache Superset or equivalent. Experience with A/B testing methodologies, statistical analysis, or experimentation platforms. Working knowledge of Trino, Iceberg. Experience with API server development and building RESTful services (e.g., Java with Spring Boot). Experience with streaming technologies such as Apache Kafka or Apache Flink.

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