Sr. Data Engineer – Data Products, Ad Platforms

Summary

Posted: Oct 15, 2024

Weekly Hours: 40

Role Number:200568505

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 Ad Platforms 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 Ad Platforms. 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.

Description

– Use modern tools and technologies to build reliable and performant pipelines and data products 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

• Background in computer science, mathematics, or similar quantitative field with a minimum of 4-6 years professional experience
• 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

Preferred Qualifications

• 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
• 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