Senior Data Engineer

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. Data Products Engineering team is seeking an ambitious and versatile Data engineer to help lead the design and scale of key data systems, delivering data products that solve exciting business problems. Responsibilities range from designing and implementing core stream-processing and batch-processing capabilities, to supporting privacy preserving critical pipelines. You will have the opportunity to define, refine, and refactor approaches, designs, and architectures to meet the data engineering challenges we must solve. You will join a team of world-class data engineers with an appetite for applying leading-edge technologies to deliver extraordinary experiences to our customers. You will play a meaningful role building data products that deliver on Apple's privacy commitments and change the way advertising works with data. You will be a leading voice in our technology strategy and its delivery, developing and mentoring team members. You will collaborate closely with the business to deliver relevant data and insight to inform our strategy and decisions. You should have 8+ years experience in data engineering roles, ideally within the ads or media space. You will have an excellent understanding of scalable approaches and thrive working in Agile environments. The ability to be a good standout colleague under tight deadline constraints is key to success!

Description

At Apple Ads, we are building the next generation of privacy-focused advertising capabilities. As a part of the data organization, we work at the cutting edge of data engineering, machine learning, and privacy at Apple's scale. We are constantly developing data products to provide amazing user experiences and to drive value for developers and publishers. As a part of this team, as a Data Engineer, you will * Engineer secure and scalable data processing systems across different execution contexts such as real-time, near real-time, and batch using Spark, Hadoop, Kafka, Cassandra and beyond * Collaborate with a team of world-class data engineers and product managers to apply leading-edge techniques and technologies that process petabytes of realtime streaming and batch events * Require a strong understanding of the intersection between business, analytics, and engineering resulting in a proactive approach, focusing on reusable solutions, to improve efficiency and time to insight * Must be able to work in a rapidly changing environment and perform effectively in a sprint-based, agile development environment * Join and contribute to a culture that emphasizes reliability, resiliency, extensibility, scalability, and productivity. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers and Apple

Minimum Qualifications

8+ years of industry experience building distributed, scalable data pipelines and data platforms Proven track record of successful and timely software product delivery with complex dependencies Demonstrated innovative, critical thinking and troubleshooting skills Excellent collaborative skills History of motivating teams to meet aggressive goals and innovate Proficiency with modern programming languages (e.g. Java/Scala/C++) and ease with picking up new technologies independently Strong computer science and data engineering fundamentals Expertise in data modeling and Iceberg lake house implementation Proficiency in distributed systems and data processing technologies (e.g. Spark, Kafka, Flink) Experience building and scaling systems on premise and in the cloud Strong technical skills with proven experience developing, architecting, and supporting scalable data infrastructure Passion for data quality, code elegance, clear documentation, cost saving and operational excellence

Preferred Qualifications

Ability to communicate effectively with cross-functional technical and non-technical teams Comfortable working in a rapidly changing environment with ambiguous requirements Comfortable with rotating on-call for mission-critical applications Prior experience in advertising industry is a huge plus!

Eeo Content

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