Senior Data Engineer - Retail Business Intelligence

Summary

Imagine what you could do here! The people here at Apple don’t just create products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things. Do you love problem solving and thinking beyond an obvious solution? Are you passionate about data accuracy and improving operational efficiency by managing complex data and information delivery? We are! The Retail Business Intelligence team is looking for a resourceful, energetic Senior Data Engineer to lead and assist with the data needs of projects by crafting creative solutions to deliver data to end users. You’ll work with cross-functional teams to stitch data from various systems into unified, high-performance and low-latency reporting layers for end-to-end analyses of projects. Join us, and you’ll help provide the data needed for the organization to effectively manage the business and improve our customer experiences across the world. Day-to-day responsibilities in the Retail Business Intelligence team include partnering with IT teams to build critical data pipelines, ad hoc data analyses, troubleshooting data and supporting project teams during all stages of projects including, requirement gatherings, gap reviews, development and testing. If you are a strategic problem solver who can lead and work with cross-functional teams to handle changes, perform data analyses, and execute project requirements to support an ever-changing data landscape, apply today!

Minimum Qualifications

Expert SQL skills with 7+ years ETL and query optimization experience Extensive Semantic layer (ESL) development experience in relational database and data lake environments Extensive experience performing data validation against complex, disparate systems Proficiency in PHP and/or Python for scripting or data manipulation, with experience creating or modifying HTML/CSS/JS-based applications, or front-end tools Professional proficiency in both Mandarin and English, written and verbal Ability to pick up new tech skills independently Bachelor’s Degree in Information Technology, Mathematics, Computer Science, or equivalent

Preferred Qualifications

Masters degree with 7+ years of experience directly related to role requirements Strong business mindset with the ability to translate business needs into technical requirements, product IT-friendly business requirements documentation, and communicate complex concepts clearly to senior leaders Structured problem solver who can break down ambiguous challenges, lead decisively under uncertainty, and provide goal-oriented direction across projects, programs, and processes Proven track record of contributing to and influencing deliverables within large global cross-functional teams, with domain experience in Retail, Finance, Operations, or Contact Center systems and datasets Proactive technologist who independently picks up new skills and drives innovation — including familiarity with modern AI practices such as embedding vectors, knowledge graphs, and agentic workflows integrated into data-driven pipelines Experience deploying applications and scripts into cloud environments (Alibaba Cloud, Tencent Cloud, AWS or equivalent)

Description

Working in a global organization, this position plays a substantial role in defining how data is structured, organized and evaluated for consistent understanding and interpretation. A key success factor for this role is the ability to understand diverse partner needs, dive deep complex data sets and propose creative solutions to senior management and business partners. In this role, you will: * Engage as a SME in global cross functional projects to ensure the planned impact will be measurable and quantifiable * Define how data is structured, organized and interpreted by building certified datasets for consistent analytics and reporting * Work closely with project managers, stakeholders and IT to deliver data requirements by leading the reporting track from requirements gathering through to successful UAT * Develop web reports and analytical tools * Define, build and deploy relevant metrics and perform ad hoc analyses * Provide consultation and training to users of analytical tools and data sets * Lead regular design and code reviews and perform debugging and coding to resolve issues * The ideal candidate has a real passion for quality and an ability to understand complex systems

Responsibilities

Own the end-to-end data engineering lifecycle for analytics in retail initiatives - from requirements gathering and data modeling through pipeline development, UAT, and production deployment - ensuring on-time, high-quality delivery across global cross-functional teams Design and maintain scalable, certified data assets across relational and data lake environments, establishing the semantic layer standards that power consistent reporting and decision-making across the organization Serve as a technical subject matter expert on multi-functional projects, partnering with IT, finance, operations, and retail stakeholders to translate complex business questions into rigorous, well-documented data solutions Lead design and code reviews, define engineering best practices, and provide mentorship and technical guidance to ensure team-wide consistency, performance, and maintainability of data pipelines and analytical tools Drive data quality and integrity by developing and enforcing validation frameworks against complex, disparate source systems, proactively identifying and resolving data issues before they surface in business-facing reporting Champion data literacy across the organization by delivering consultation, training, and documentation that enable business partners to independently leverage analytical tools and certified datasets with confidence