Big Data Analyst, Analytics & Data Engineering -Apple Service Engineering

Seattle, Washington, United States
Software and Services

Summary

Posted:
Weekly Hours: 40
Role Number:200536150
The Apple Service 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, Apple Books, Apple Pay. And they do it at a massive scale, meeting Apple’s high expectations with dedication to deliver a variety of entertainment in over 35 languages to more than 150 countries. Do you have a passion for data and how it can be used to improve customer experience, protect user privacy, make products better, and increase revenue for a business? Do you thrive working with data engineers, data scientists and project managers in an agile, distributed and project focused work environment? If so, join us! Apple is seeking an experienced data analyst to work on an exciting set of problems outstanding to ASE. You will help find interesting data trends, identify root causes, and help transform up-and-coming ideas to products and systems. You will do so in an environment that highly values collaboration, mentoring and continuous learning.

Key Qualifications

  • 5+ years in an analytics or data engineering role
  • Background in data analytics, proficient in SQL or Python Pandas
  • Experience with data visualization tools, such as Tableau, GGplot, Keynote etc
  • Fundamental understanding of statistical analysis, forecasting and modeling
  • Experience in coding for automation (e.g. Scala, Python, Java etc.)
  • Familiarity with writing data pipelines using one or more big data technologies (e.g. Spark, Hive, Trino, Flink, Airflow etc.)
  • Familiarity with modern cloud technologies such as Kubernetes
  • Familiarity with commerce, payments, and user experience datasets at online services
  • Excellent written and verbal communication skills

Description

- Dive deep into large-scale data to uncover trends and identify key insights - We build and automate dashboards used to present key insights to partners - Partner with data engineers and project managers to conduct data investigation analysis - Collaborate with researchers and machine learning engineers for building data science and machine learning solutions such as anomaly detection - Facilitate multi-functional discussion to find out what is the right technical resolution to the business problems

Education & Experience

Bachelors or higher degree in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Operations Research or a related field)

Additional Requirements

Pay & Benefits