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 Software Engineer, Analytics Engineering - Payments Gift Card Analytics - Seattle, Washington, 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
Computers - Platforms
Computers - Networks
Computers - Software Engineer
 
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: 200284653 / Latpro-3822130 
Date posted: Sep-08-2021
State, Zip: Washington, 98199

Description

Software Engineer, Analytics Engineering - Payments Gift Card Analytics

Seattle , Washington , United States

Software and Services

Summary

Posted: Sep 7, 2021

Weekly Hours: 40

Role Number: 200284653

The Apple Media Products Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology! These are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apple's high expectations with high performance to deliver a huge variety of entertainment in over 35 languages to more than 150 countries!These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services. Thanks to Apple's unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, forward-thinking, and cross-functional, offering greater exposure to the array of opportunities here. Are you passionate about communicating with data effectively? Curious how data is manipulated in real-time? Want to utilize cutting-edge machine learning techniques to detect anomalies in a sea of data? This is the team to join. You'll be exposed to modern, open-source technologies that are standard to the big data industry, and will work with data at a scale that few organizations in the world have access to.

Key Qualifications

  • Experience in designing and developing large scale, batch and streaming, big data pipelines
  • Knowledge in building and deploying large scale applications in Cloud based environment
  • Highly proficient in Java and other object-oriented languages like Scala and/or C#, or similar
  • Confidence with SQL databases like Vertica, Oracle, Snowflake and NoSQL databases like Cassandra
  • Experience managing data in relational databases and developing data pipelines using advanced SQLs and scripts
  • Demonstrate proficiency in data management and automation on Spark, Hadoop, and HDFS environments
  • Experience driving product features, functional specifications, and development schedules, represent team and technology
  • Passion and prior experience designing and implementing outstanding large distributed systems
  • Excellent debugging, critical thinking, and interpersonal skills
  • Proven documentation and technical writing skills

Description

Data drives the direction and strategy for Apple's growing Services business. As the Gift Card Analytics Engineering team we collect, curate, and provide insights into Apple Gift card data from Apple's services, Online Store, and Retail organizations. This data plays a critical role in enabling business growth. We build data pipelines with maximum efficiency, scalability and reliability to allow domain specific engineers to focus on their specialties. Our data is used to provide best customer experience while buying Apple products using Apple Gift cards. We've even built data products and visualizations to be consumed by business partners at Apple. You will be working with a dynamic team valuing collaboration, brainstorming, with an emphasis on optimized design. You will be responsible for developing systems, tools, and visualizations to make sense of the data. We are looking for a sharp engineer who also has a keen sense of how to build quality and scalable products. You are also a team player -- ready to engage in lively design discussions, and able to give and receive constructive code reviews. Your curiosity drives you to explore new technologies and apply creative solutions to problems. The ideal candidate pays close attention to details, but also keeps sight of the bigger picture. We are looking forward to a new enthusiastic member to join our group!

Education & Experience

Master's or Bachelor's degree in Computer Science or a related field, or equivalent experience. Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.

Additional Requirements

  • Be an advocate and driver for performance optimization, automation, and unit tests
  • Proficiency with source control systems (SVN, Git) and build tools such as Gradle, Maven, etc.
  • Solid hands on experience with the Big-Data ecosystem (Spark, Hadoop, Hive, Pig, etc.)
  • Built and deployed large scale data pipelines (e.g. Kafka, Spark, Storm)
  • Understands different data storage solutions and when to use them (e.g. RDBMS, Cassandra, Solr, Redis)
  • Experience implementing and administering logging, telemetry and monitoring tools like Splunk is a plus
  • Passionate about being a part of a tight-knit fast moving Big data team
  • Demonstrable understanding of development processes and agile methodologies





Requirements

See job description

 

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