Job Details

Weekly Hours: 40

Role Number: 200649215-2459

Summary

At Apple, we believe in the power of technology to enrich people's lives. Everything we build is designed to empower people, including our advertising platform. We deliver ads in a way that benefits both customers and advertisers — helping people discover content, supporting creators, and protecting and respecting everyone’s privacy. Our technology makes advertising possible on the App Store, Apple News, Stocks, and Apple TV. We help developers and marketers of all sizes drive app discovery across the App Store. Our display ads on Apple News and Stocks let advertisers promote their products alongside trusted content from the world’s best journalists. Sponsorship integrations and experiences in live sports on Apple TV help advertisers connect with passionate fans. Everything we do is with the unwavering commitment to privacy you expect from Apple. Because when advertising is done right, it benefits everyone!

Description

The Apple Ads Data Products Engineering team is seeking a senior data engineer to join in developing the next generation of data products and analytical solutions built to empower Algo, Product, Data Insights, Sales, Marketing and Executive teams. In this role you will be a key member of the team driving the strategy, development, execution, and continuous improvement of core algo and analytical data products for Apple Ads. You will be building the foundational data architectures and pipelines for our algo and data science capabilities. You will join a team of world-class data engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our data consumers. A successful candidate will have experience building data pipelines using varied engineering technologies such as AWS, EMR, EKS, Spark, Hive, SQL, Iceberg, Snowflake, Oracle, Airflow, Datadog

Minimum Qualifications

• BS/MS in Computer Science, Distributed Systems, Software Engineering, or related field; and experience designing, building, maintaining, and extending web-scale production systems.

• Background in computer science, mathematics, or similar quantitative field with a minimum of 5 years deep experience on the required tech stack

• Demonstrated ability to implement and extend highly performant, resilient, and reliable data services

• Worked in cloud environments and are familiar with object stores, and other common cloud-native data storage and processing frameworks

• Extract Transform Load (ETL) and streaming experience using Spark, Kafka, Hive, Iceberg, or similar technologies at petabyte scale

• Deep expertise in data modeling, Scala, Spark, Python, Java, Scala, SQL, Trino, Glue and/or other relevant languages and frameworks

• Experience with workflow scheduling / orchestration such as Airflow

• Ability to take requirements from design through to implementation both independently and working collaboratively within teams

• Ability to work closely with operational teams on deployment, monitoring, management concerns

Preferred Qualifications

• Ability to design and implement effective testing and operations strategies for data pipelines and data products

• Worked in CI/CD environments

• Experience with applying data encryption and data security standards

• Experience using one or more scripting languages (e.g., Python, bash, etc.)

• Experience supporting and working with cross-functional teams in a dynamic environment

• Understanding of modern data engineering approaches and are aware of what leading players are doing

• Experience implementing machine learning and data science workloads a plus

• Ability to communicate technical concepts to a business-focused audience

• Most importantly, a sense of humor and an eagerness to learn

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .