Are you excited about using data to shape the experience of products used by hundreds of millions of people around the world? The AIML Data Engineering team, part of Apple’s AIML Evaluation organization, builds scalable and reliable data infrastructure that powers Siri, Search, and Machine Learning across Apple. We’re looking for collaborative and mission-driven data engineers who care deeply about data quality, user impact, and building at scale. If you’re passionate about tackling complex data challenges, eager to work with petabytes of data, and inspired by Apple’s commitment to privacy and innovation, we’d love to hear from you.

DESCRIPTION

In this role, you’ll work cross-functionally across product and data science teams to build large-scale batch and streaming data pipelines that power Analytics, Experimentation, and Machine Learning. You’ll design instrumentation on both client and server sides to ensure accurate and reliable data collection. You’ll validate that data flows with the right structure, frequency, and quality. You’ll build clean, high-performance data models and develop self-serve tools that make data easier to consume and scale. You’ll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights.

MINIMUM QUALIFICATIONS

• 7+ years of experience designing, building, and maintaining distributed data processing systems at scale.
• 5+ years of hands-on experience with batch and/or streaming data technologies such as Spark, Flink, Kafka, Presto, Hadoop and Iceberg.
• Strong data modeling and SQL skills and experience working with large-scale, complex, and high-dimensional datasets.
• Proficient in at least one modern programming language (e.g., Python, Java and Scala).

PREFERRED QUALIFICATIONS

• MS or BS in Computer Science, Engineering, Math, Statistics, or a related field or equivalent practical experience in data engineering.
• Experience with machine learning algorithms or pipelines, particularly in the context of data engineering.
• Experience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus.
• Familiarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing).
• Proven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices.
• Comfortable working independently in a fast-paced, ambiguous environment.
• Excellent communication and problem-solving skills.

Please refer the Job description for details