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Software Engineer (Data Analytics), AI & Data Platforms (AiDP)
About the position
Apple's AI & Data Platform (AiDP) Data Services organization is seeking a motivated Software Engineer, Data Analytics focused on providing data analytics and search services. Engineers on this team build data processing platforms and develop required tooling for Apple's most critical internet services at massive scale. In AiDP, your work will benefit hundreds of millions of users. AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning — including generative AI — along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.
Responsibilities
- Build data processing platforms and develop required tooling for Apple's most critical internet services at massive scale.
- Support data processing and migration efforts across hybrid-cloud environments (On-Prem ↔ AWS ↔ AliCloud) following established Runbooks and adhering to local data residency and regulatory requirements (e.g., China's Cybersecurity Law and PIPL).
- Communicate and collaborate with infrastructure teams and colleagues across a distributed team.
Requirements
- 3+ years experience in data analytics and/or data search space
- Experience and knowledge of Java or Python programming languages
- Hands-on production experience with at least one of the following technologies: Solar, Elastic Search, Iceberg, ClickHouse, Doris and/or Couchbase
- Exposure to running infrastructure with reliance on automation tooling, across Datacenter and Cloud architectures (including Alibaba Cloud and/or AWS)
- Bachelor's or Master's degree in Computer Science or a related work experience
Nice-to-haves
- Some operational experience with stateful services on Kubernetes
- Exposure to database-as-a-service control planes, provisioning APIs, or self-service tooling
- Experience assisting with cross-cloud / hybrid-cloud data migrations for transactional systems
- Familiarity with observability concepts (SLIs/SLOs), backup, and DR practices for OLTP/distributed-SQL engines
- Solid troubleshooting skills, a resourceful first-principles approach to problem solving, and good technical writing habits
- Contributions to open-source database projects or internal data-platform tooling