Data Engineer
3 Months ago • All levels • $143,100 PA - $264,200 PA
Data Analysis
Job Description
The Ad Platforms Data team at Apple is looking for a Data Engineer to build high-performance data stores for next-generation analytical solutions. This role involves developing, executing, and improving core data infrastructure and processes. The Data Engineer will play a key role in the design and development of the data model, pipelines, and data warehouse implementation supporting various customer experiences and analytics. They will enable teams of architects, engineers, analysts, data scientists, and business users. Responsibilities include building data processing pipelines, data models, and working with cloud-based data warehouse platforms.
At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is crafted for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. The Ad Platforms Data team is seeking a Data Engineer specializing in building high performance data stores to enable next generation analytical solutions. In this role, you will work as a key member of a data-centric team to drive the development, execution, and continuous improvement of core data infrastructure and processes. You will have a key role in the joint design and development of the data model, pipelines, implementation and delivery of the analytical data warehouse supporting our suite of customer experiences in addition to ad hoc and sophisticated analytics. You will be a key enabler for teams of architects, engineers, analysts, data scientists, and business users. A successful candidate will have experience building data processing pipelines, data models and handling cloud based data warehouse platforms.
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