Software Data Engineer

\\nPeople at Apple don't just build products - they craft the kind of experience that has revolutionized entire industries. The diverse collection of our people and their ideas inspire innovation in everything we do. Imagine what you could do here! Join Apple, and help us leave the world better than we found it.\\nThe Analytics Platforms & Experiences (APX) team is at the forefront of revolutionising Data Engineering. We drive significant increases in efficiency and productivity through a flawless ecosystem of frameworks and products that unlock observability, knowledge and enable data quality-driven orchestration at scale. APX is part of the broader Apple Services Engineering division that powers App Store, Apple TV+, Apple Music, Apple Podcasts, Apple Books, Fitness+, the iTunes Store and more.\\nThe APX Bedrock team is the foundational platform layer within APX, responsible for building the systems and services that underpin data engineering excellence across the organization. We are looking for a Software Data Engineer to join our team and contribute to building modern data platform capabilities. In this role, you will work on systems that enable data engineers across Apple to build applications efficiently while maintaining high standards of data quality, reliability, and operational excellence. You will have the opportunity to work with cutting-edge data technologies and grow your expertise in AI-enhanced engineering practices.\\n

As a Software Data Engineer on the APX Bedrock team, you will be a hands-on contributor building and enhancing the platform services that power data engineering at Apple. You will work closely with senior engineers and architects to deliver reliable, scalable solutions that have a tangible impact on data teams across the organization.\n\n* Design, develop, and maintain Java-based backend services and APIs that support core platform capabilities including metadata collection, dataset lifecycle management, and orchestration\n* Build and optimize data processing pipelines using distributed computing frameworks\n* Design and implement data models that accurately represent complex domain concepts and support efficient querying and storage patterns\n* Implement systems for monitoring dataset health, tracking completeness, and enforcing quality standards\n* Write clean, well-tested, production-quality code in Java as the primary language, with Scala, Go, or Python as complementary skills\n* Own database design decisions including schema design, indexing strategies, and query optimization for both relational and non-relational data stores\n* Participate in operational responsibilities including on-call rotations, incident response, and system health monitoring\n* Collaborate with peer teams across the platform organization to integrate and deliver cohesive capabilities\n* Leverage AI-powered development tools to accelerate development and improve code quality\n* Engage with internal users to understand their needs and translate feedback into platform improvements\n\n

Bachelor's Degree in Computer Science, Engineering, or equivalent related experience\n3+ years of hands-on experience building data applications, backend services, or platform services\nStrong, production-level programming experience in Java, including building and maintaining RESTful or RPC-based services\nSolid experience with relational databases including schema design, data modeling, and query optimization using SQL\nExperience with distributed data technologies such as Apache Spark or Apache Flink, Hadoop, HDFS, Kafka\nFamiliarity with workflow orchestration concepts and tools such as Apache Airflow\nDemonstrated ability to build, test, and operationally maintain reliable software systems in production environments

Experience with non-relational or NoSQL databases and understanding of when to apply different data storage paradigms\nProficiency in Scala, Go, or Python as complementary programming languages\nFamiliarity with container orchestration tools such as Kubernetes\nExposure to AI-powered development tools and practices (e.g., Claude Code, Copilot)\nExperience with data quality monitoring, metadata management, or dataset lifecycle tracking\nUnderstanding of streaming data architectures and real-time processing patterns\nExperience with event-driven architectures and distributed messaging systems\nStrong communication skills and comfort collaborating across teams\nCuriosity and eagerness to learn new technologies and take on increasing responsibility