Data Engineer, Apple Ads

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 designed 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.
rmant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy.

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 advanced 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 managing cloud based data warehouse platforms.

Minimum Qualifications

Minimum 1+ years experience in Cloud Data Engineering, preferably with a background in computer science, mathematics, or a related quantitative field.
Expertise in building Cloud Data Warehouses in Snowflake, Redshift, BigQuery or analogous architectures.
Deep SQL expertise, data modeling, dimensional modeling and experience with data governance
Experience with the practical application of data warehousing concepts, methodologies, and frameworks
Experience using data processing tools and technologies such as Python, Spark, Talend, Informatica, SSIS or DBT
Embrace data platform thinking, design and develop data pipelines keeping security, scale, uptime and reliability in mind
Able to confidently express the benefits and constraints of technology solutions to technology partners, stakeholders, and team members.
Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications

Experience designing and operating petabyte-scale data processing systems.
Deep expertise in Apache Spark performance tuning and optimization.
Experience with both batch and real-time/streaming architectures, including Kafka and/or Flink.
Experience building data platforms or processing frameworks that are reused by multiple teams or pipelines.
Experience with AWS technologies, including S3 and Kubernetes/EKS or equivalent cloud platforms.