Senior Data Engineer, Retail Business Intelligence

Apple

About The Position

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. 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.

Requirements

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
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)

Responsibilities

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
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