Are you excited about using data to shape the experience of products used by hundreds of millions of people around the world? \\nThe Evaluation Data Engineering team, part of Apple's SWE organization, builds the scalable and reliable data platform that powers Siri, Search, and Machine Learning across Apple.\\nWe're looking for collaborative and mission-driven software engineers who care deeply about data quality, user impact, and building at scale. \\nIf 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.\\n \\n\\n
In this role, you'll work cross-functionally across product and data science teams to build large-scale stream and batch processing data pipelines that power Analytics, Experimentation, and Machine Learning. \nYou will design a unified and groundbreaking data processing framework using Flink, and/or Spark. \nYour work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the framework's capabilities to new user scenarios and groundbreaking machine learning applications. \nYou will collaborate closely with Siri, Search, and other teams to design solutions that transform raw data into datasets that drive innovation. \nYou'll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights.\n \n\n \n
7+ years of experience designing, building, and maintaining distributed data processing systems at scale.\n5+ years of hands-on experience with stream and/or batch processing technologies such as Flink, Spark, Kafka, Airflow, Iceberg, and Trino.\n2-3 years of experience in full-stack development\nProficient in at least one modern programming language (e.g., Java, Scala, and Python).\nMS or BS in Computer Science, Engineering, Math, Statistics, or a related field, or equivalent practical experience in data engineering. \n\n
Strong in algorithms, data structures, data modeling, and SQL, with experience working on large-scale, complex, and high-dimensional datasets.\nExperience with machine learning algorithms or pipelines, particularly in the context of data engineering.\nExperience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus.\nFamiliarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing).\nProven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices.\nComfortable working independently in a fast-paced, ambiguous environment.\nExcellent communication and problem-solving skills.\n
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 69a3f554a8f65222a6a3956b973e6673
- Posted 5 hours ago
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