Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your work, and there's no telling what you could accomplish.
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. As a Senior Data Engineer on the team, you'll design and build the data warehouses, pipelines, and analytics that power decisions across Apple, working closely with teams in the US and around the world.
Description
Design, build, and manage cloud-based data warehouses and data access layers that support teams across Apple.
Develop highly scalable and secure ETL pipelines to ingest, process, and serve data from a multitude of source systems.
Perform data discovery and in-depth analysis across large, multi-source datasets, quickly learning new data to uncover insights and validate quality.
Build proofs of concept and run ad-hoc and recurring analyses to answer high-priority business questions.
Analyze and optimize existing data systems and queries, including Spark and Trino, for reliability, performance, and cost at scale.
Use modern AI tools to enhance and automate data workflows such as orchestration, scheduling, and monitoring.
Collaborate closely with US-based and regional teams and business partners, presenting findings and recommendations in English.
Preferred Qualifications
Demonstrated ability to apply AI-powered tools and methods to improve data pipeline efficiency and reliability
Detailed understanding of OLTP and OLAP systems and when to apply each
Hands-on experience with both relational and NoSQL database systems
Proven ability to translate complex business requirements into scalable, data-driven solutions
Strong project management and presentation skills, with the ability to deliver findings to multiple levels of stakeholders
Minimum Qualifications
Bachelor's degree in Computer Science, related field, or equivalent practical experience
3+ years of professional experience in data engineering, building and operating data pipelines and data warehouses
Expert proficiency in SQL, including query optimization, and strong Python for data processing and automation
Hands-on experience with big data and distributed systems, including Spark and Trino
Experience building ETL pipelines and working with cloud data platforms such as Ali Cloud (or equivalent)
Strong data discovery and analysis skills, with a proven ability to learn new data quickly, uncover insights, and validate data quality
Deep understanding of data warehouse architecture and dimensional modeling principles
Strong English proficiency, able to communicate and collaborate effectively with US and global teams in English
