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 Data Engineer - Ad Platforms Engineering - Austin, Texas, United States

Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Computers - Programming Languages
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200208761 / Latpro-3763006 
Date posted: Nov-21-2020
State, Zip: Texas, 78729


Data Engineer - Ad Platforms Engineering

Austin , Texas , United States

Software and Services


Posted: Nov 20, 2020

Role Number: 200208761

At Apple, we work every day to create products that enrich people's lives. Our Ad Platforms group makes it possible for people around the world to easily access informational and imaginative content on their devices while helping publishers and developers promote and monetize their work. Our technology and services power Search Ads in the App Store and the advertising found in Apple News. Our platforms are highly performant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy! The Ad Platforms Data Insights Engineering team is seeking a data engineer to join in developing the next generation of analytical solutions built to empower Sales, Product, and Executive teams. This role plays as a key member of the team driving the strategy, development, execution, and continuous improvement of data products for Ad Platforms. You will be building the foundational data architectures and pipelines for our core analytical data products & science capabilities. A successful candidate will have experience using varied data storage such as Hadoop, Cassandra, and Oracle as well as analytical and processing technologies such as Spark and Hive.

Key Qualifications

  • Background in computer science, mathematics, or similar quantitative field with a minimum of 4-6 years professional experience
  • Experience supporting and working with cross-functional teams in a dynamic environment
  • Extract Transform Load (ETL) experience using Spark, Kafka, Hadoop, or similar technologies
  • SQL expertise, data modeling, and relational database experience required
  • Experience using one or more scripting languages (e.g., Python, bash, etc.)
  • Presto, Hive, SparkSQL, Cassandra, Solr, or other big data query and transformation experience
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Athena, Glue, Sagemaker
  • Unix-based command line experience required
  • Experience with workflow scheduling / orchestration such as Airflow or Oozie
  • Experience with applying data encryption and data security standards
  • Ability to design and implement effective testing and operations strategies for data pipelines and data products
  • Experience implementing machine learning and data science workloads a plus
  • Data visualization experience using R, Python, or Tableau a plus
  • Data visualization or web development skills a plus
  • Ability to communicate technical concepts to a business-focused audience
  • Most importantly, a sense of humor and an eagerness to learn


- Solve tough problems across the technology spectrum including designing, creating, and extending data storage, processing, and analytic solutions - Partner with business and analytics teams to understand specific requirements, build, and deploy analytical pipelines and data science workloads - Use modern tools and technologies to build reliable and performant pipelines and data products - 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

Education & Experience

- Bachelor's degree or equivalent experience required, Master's Degree in Computer Science or other Engineering field strongly desired


See job description


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