What are the responsibilities and job description for the Data Engineer, App Insights Engineering, Services Data Science & Analytics position at Apple, Inc.?
Are you ready to make a significant impact at the intersection of data engineering and App Store analytics within Apple? If you are passionate about building robust data pipelines, crafting complex data models, and enabling compelling, data-driven insights at scale, we would love for you to apply! The Apple Services Data Science & Analytics organization drives decisions that improve the customer experience, accelerate growth, and uncover new business opportunities while respecting user privacy and adhering to regulatory policy.
We work on some of the largest e-commerce and media streaming businesses in the world and have an incredible team collaborating on the best ways to improve these services for our customers! Our culture is built on rapid iteration, open debate, and independent thinking - we take calculated risks and work as analytical advisors across product, design, engineering, marketing, editorial, legal, and business teams.
5 years of experience in data engineering or business intelligence roles, with demonstrated expertise building and maintaining complex data pipelines and data models at scale\nStrong proficiency with SQL and proven experience querying, manipulating, and analyzing internet-scale data structures and very large datasets\nDemonstrated experience with data engineering tools and concepts, including pipeline development, data model design, and aggregation strategies in support of analytics and reporting\nExceptional written and verbal communication skills, with the ability to translate complex data concepts for diverse audiences including product, business, and engineering stakeholders\nStrong time management skills with the ability to balance multiple projects with competing priorities\nBS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field
Experience in a fast-paced technology company, digital subscription business, or large-scale App Store or e-commerce platform, navigating complex data ecosystems\nAdvanced proficiency with Python or similar languages, and experience with distributed computing frameworks (e.g., Spark) for complex data manipulation and analytics\nFamiliarity with data governance, data quality frameworks, or metadata management concepts\nMS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field
We work on some of the largest e-commerce and media streaming businesses in the world and have an incredible team collaborating on the best ways to improve these services for our customers! Our culture is built on rapid iteration, open debate, and independent thinking - we take calculated risks and work as analytical advisors across product, design, engineering, marketing, editorial, legal, and business teams.
5 years of experience in data engineering or business intelligence roles, with demonstrated expertise building and maintaining complex data pipelines and data models at scale\nStrong proficiency with SQL and proven experience querying, manipulating, and analyzing internet-scale data structures and very large datasets\nDemonstrated experience with data engineering tools and concepts, including pipeline development, data model design, and aggregation strategies in support of analytics and reporting\nExceptional written and verbal communication skills, with the ability to translate complex data concepts for diverse audiences including product, business, and engineering stakeholders\nStrong time management skills with the ability to balance multiple projects with competing priorities\nBS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field
Experience in a fast-paced technology company, digital subscription business, or large-scale App Store or e-commerce platform, navigating complex data ecosystems\nAdvanced proficiency with Python or similar languages, and experience with distributed computing frameworks (e.g., Spark) for complex data manipulation and analytics\nFamiliarity with data governance, data quality frameworks, or metadata management concepts\nMS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field