Data Engineer at Apple

Beijing, Beijing, China -

Full Time

Start Date

Immediate

Expiry Date

06 Apr, 26

Salary

0.0

Posted On

06 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Modeling, Pipeline Development, Software Engineering, Dimensional Modeling, Data Warehouse Architecture, Relational Database Systems, NoSQL Database Systems, Linux Environments, Python, SQL, Big Data Technologies, Cloud Data Services, Problem-Solving, Communication Skills, Statistical Models, Forecasting

Industry

Computers and Electronics Manufacturing

Description

Apple is where outstanding talents come together to do the best work of their lives. Together, we build products and experiences that were once unimaginable—and are now indispensable. If you’re driven by the chance to create a meaningful impact and thrive in one of the world’s most diverse and inclusive work environments, a career at Apple could be your dream opportunity. At Apple, we value hard work, a collaborative environment, and the creativity that arises when talented individuals from varied backgrounds approach challenges with different perspectives. Our teams don’t just build products—we redefine industries, turning groundbreaking ideas into reality. It’s this diversity of people and thought that fuels the innovation behind everything we do, from cutting-edge technology to our industry-leading environmental initiatives. Join us, and help make the world better than we found it. At Apple, new ideas quickly evolve into extraordinary products, services, and customer experiences. Bring your passion and dedication, and there’s no limit to what you can achieve. This is a high-visibility, critical role within Apple China, with significant influence over the Sales Team. The successful candidate will be responsible for interpreting quantitative data, developing statistical models, and forecasting demand to support sales analytics and strategic decision-making. DESCRIPTION Design and build cloud-based data warehouses to deliver efficient analytical and reporting capabilities for Apple’s global and regional sales and finance teams. Develop highly scalable data pipelines to ingest and process data from multiple source systems, leveraging Apache Airflow for workflow orchestration, scheduling, and monitoring. Architect generic, reusable solutions that enforce to data warehousing best practices while addressing complex business requirements. Analyze and optimize existing systems, providing improvements and ongoing support as needed. Uphold the highest standards of data integrity and software quality, ensuring reliable and accurate outputs. We are looking for a proactive self-starter who takes initiative, learns fast, and works well across teams. Join our growing team where no two days are the same - solving tough technical challenges and business problems in a fast-paced environment. MINIMUM QUALIFICATIONS 3+ years of professional experience in data modeling, pipeline development, and software engineering Proficiency in dimensional modeling and data warehouse architecture Hands-on experience with both relational and NoSQL database systems Solid understanding of Linux environments with scripting capabilities in Python and SQL PREFERRED QUALIFICATIONS Detailed understanding of OLTP and OLAP systems Experience with big data technologies (Kafka, Spark, Flink, Hive, etc.) Practical knowledge of cloud data services (AWS, Ali Cloud, or equivalent platforms) Demonstrated ability to analyze business requirements and deliver data-driven solutions Excellent written and verbal communication skills with strong problem-solving abilities A Bachelor’s or equivalent experience or Master’s degree in Computer Science, Computer Engineering, or a related technical field—or equivalent practical experience.

Responsibilities

The successful candidate will design and build cloud-based data warehouses and develop scalable data pipelines to support sales analytics. They will also analyze and optimize existing systems while ensuring data integrity and software quality.