Apple Services Engineering (ASE)’s Solutions Architecture & Platform team is seeking a versatile and highly skilled Staff Software Engineer to design, develop, test, and support software solutions across our platform ecosystem. Our platforms provide secure, reliable, and scalable infrastructure for processing metadata and enabling business operations across Apple’s internal services. This includes supporting the delivery of digital content to storefronts, powering reporting systems, and building internal tools and applications. In this role, you will help design and implement scalable data infrastructure, containerized environments, and intelligent content systems. You'll work across real-time data pipelines, test data automation, and machine learning-driven metadata and documentation tools. The problems we solve are complex and impactful, requiring technical depth, strategic thinking, and a passion for tackling challenges at scale. If you thrive at the intersection of distributed systems, data engineering, and intelligent automation, this is your opportunity to shape the future of Apple’s content and analytics platforms.
Requirements
- Full-Stack Development experience, including backend systems (Java, Spark SQL) and frontend frameworks (React), with knowledge of distributed search engines like SOLR.
- Proficiency in Java and strong understanding of distributed systems and backend development.
- Hands-on experience with stream processing (e.g., Kafka, Flink, Spark Streaming).
- Practical knowledge of data lake architectures, especially Apache Iceberg or similar formats.
- Experience with CDC pipelines and integrating diverse database systems (e.g., Oracle, Postgres, NoSQL).
- Proven ability to develop and manage Dockerized applications and deploy in Kubernetes environments.
- Experience working with large-scale data pipelines, schema evolution, and metadata management.
Responsibilities
- Develop transformation platform to unify change data capture (CDC) streams from heterogeneous source systems and deliver them to a centralized data lake in Iceberg format, supporting both initial ingestion and incremental updates.
- Build a platform for on-demand, containerized test environments that load targeted data into isolated databases using minimal input.
- Modernize and optimize a self-service data exploration platform by contributing across backend, middleware, and frontend layers, while enabling near real-time data updates through streaming pipelines.
- Collaborate on machine learning-based systems to automate metadata generation and support natural language interfaces for querying data.
- design resilient systems, standardize data pipelines, and enable scalable, intelligent solutions across the company.
- gathering and refining requirements, designing solutions, writing and testing code, and integrating services to ensure an exceptional user experience.
- contribute to prototyping efforts, mentor team members, participate in design and code reviews, and support incident analysis.
Other
- 10+ years of software or data engineering experience.
- Bachelor of Science in Computer Science or Equivalent
- Familiarity with ML/LLM solutions for metadata, NLP querying, or intelligent documentation systems.
- Background in test data automation and containerized database environments.
- Experience building enterprise-grade search and indexing systems.
