Data Engineer - Targeting Engineering, Apple Ads at Apple

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

0.0

Posted On

13 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, AWS, Spark, Hive, SQL, Iceberg, Snowflake, Airflow, Java, Python, ETL, Kafka, Distributed Systems, CI/CD, Data Security, Machine Learning, AdTech

Industry

Computers and Electronics Manufacturing

Description

At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. The Apple Ads Targeting Engineering team is seeking a data engineer to join in developing the next generation of privacy preserving solutions. In this role you will be a key member of the team driving the development, execution, and continuous improvement of core pipelines and infrastructure. 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, and Datadog. DESCRIPTION - Use modern tools and technologies to build reliable and performant pipelines and infrastructure with extreme scale requirements - Solve tough problems across the technology spectrum including designing, creating, and extending data storage, processing, and analytic solutions - Automate and optimize existing analytic workloads by recognizing patterns of data and technology usage - Must be able to work in a rapidly changing environment and perform effectively in a sprint-based agile development environment MINIMUM QUALIFICATIONS 3+ years of professional experience and background in computer science, mathematics, or similar quantitative field Proficiency in Java as well as other relevant languages and frameworks (Spark, Python, SQL, Trino, Glue) Demonstrated ability to implement and extend highly performant and resilient data services Worked in cloud environments and are familiar with object stores, and other common cloud-native data storage and processing frameworks Experience working with distributed systems (Cassandra, Kubernetes, Docker, etc.) Extract Transform Load (ETL) and streaming experience using Spark, Kafka, Hive, Iceberg, or similar technologies at petabyte scale Experience with workflow scheduling / orchestration such as Airflow, DBT, etc. 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 BS/MS in Computer Science, Distributed Systems, Software Engineering, or related field; and experience designing, building, maintaining, and extending web-scale production systems 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 Experience in AdTech highly desirable Most importantly, a sense of humor and an eagerness to learn

Responsibilities

The data engineer will develop and improve core pipelines and infrastructure for privacy-preserving solutions. They will work on building reliable and performant data pipelines and solve complex problems across various technologies.