Analytics Data Engineer - App Store

Apple’s App Store is the world’s largest and most innovative app marketplace, home to 2.1 million apps and serving more than 850 million customers every week across all the Apple devices. Since the App Store launched in 2008, it has changed how we all live; it has enabled countless new companies, spawned new industries, and built millions of jobs. In a world where apps have become essential in people’s daily lives, the App Store team has become essential to Apple’s business.

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, and fostering such values across developer community. We keep innovating privacy technologies and lead the world into a safer future where you control what data is collected about you.

Although App Store is 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. In this role you will help deliver great experience and improve the store for both users and developers by generating insights from data in a privacy-friendly manner.
As a member of the App Store Data Engineering team, you will play a key role in building large-scale data products for external reporting needs.
This is a software engineering role with strong analytical responsibilities. We build robust, production-quality code and process petabytes of data daily in a distributed way.
Data is our core product, and we care deeply about its correctness, semantic, lineage, usability and future evolution.
<h3>Minimum Qualifications</h3>5+ years of hands-on experience in data engineering, analytics engineering, distributed data processing, or similar roles
5+ years of hands-on experience in Java or Scala
3+ years of hands-on experience in building and maintaining service layer applications, including data access patterns and integration with backend data systems
Expert-level proficiency in SQL
Good understanding of computer science fundamentals — algorithms, data structures, complexity
Good record of maintaining systems and apps in production
Bachelor or Master degree in Computer Science, Software Engineering, Business Information Systems, Statistics or similar quantitative degree, or equivalent work experience
<h3>Preferred Qualifications</h3>Excellent communication and collaboration skills and ability to present new ideas
Deep understanding of big-data stack, experience with some or all of following technologies: Spark, Flink, Kafka, Trino(Presto), Hadoop, Airflow, Iceberg, DBT, Snowflake, Cassandra, HBase, S3-like blob storage, Redis and other similar systems
Experience with traditional RDBMS systems: Oracle, PostgreSQL or others
Understanding e-Commerce domain: payments, transactions, sales, subscriptions, monetization, etc
Ability to work autonomously and unblock yourself
Experience of working in corporate environments with big number of teams
Data investigation and exploration skills
System design and documentation skills