Apple Big Data Engineer, Enterprise Systems in Austin, Texas
Big Data Engineer, Enterprise Systems
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Posted:Nov 19, 2023
Role Number: 200523479
Do you love understanding every detail of how new technologies work? Join the team that serves as Apple’s nerve center, our Information Systems and Technology group. There are countless ways you’ll contribute here, whether you’re coordinating technology needs for product launches, designing music solutions for retail locations, or ensuring the strength of in-store Wi-Fi connections. From Apple Pay to the Apple website to our data centers around the globe, you’ll help design and manage the massive systems that countless employees and customers rely on every day. You’ll also build custom tools for employees, empowering them to solve complex problems on their own. Join our team, and together we’ll explore all the ways to improve how Apple operates, freeing our employees to do what they do best: craft magical experiences for our customers. The Global Business Intelligence team provides data services, analytics, reporting, and data science solutions to Apple’s business groups, including Retail, iTunes, Marketing, AppleCare, Operations, Finance, and Sales. These solutions are built on top of an extraordinary data platform and leverage multiple frameworks. This is an extraordinary opportunity for a proficient, experienced, and results-oriented cloud engineer to define and build some of the best-in-class frameworks and tools for Apple’s private and third party clouds!
5+ years of programming experience Java, Scala or Python
In-depth knowledge of Spark, Ray or other distributed computing frameworks
Understanding of SQL query engines like Trino, Hive etc.
Experience with Docker, Kubernetes or EKS
Experience with debugging issues on distributed systems.
Knowledge of software engineering practices and standard methodologies for the full software development lifecycle
Experience with public cloud (AWS/GCP)
Have created frameworks to deploy platforms in AWS/Azure/GCP.
Good understanding of AI/ML stack - GPUs, MLFlow, LLM models is plus.
Experience in building, tuning, scaling, and monitoring applications to process real-time, near-real-time and batch data
Understanding of data modeling, data warehousing, and ETL concepts is a plus
The GBI Big Data Engineering team is responsible for building and managing data platforms at scale on Cloud, that help Apple process, store and access petabytes of data. We’re looking for a Big Data Engineer with strong understanding of big data and ML platforms, passionate about building and managing cloud infrastructure and can demonstrate to Apple’s high standards. As a part of our team, you’ll be responsible for building and integrating various compute and storage infrastructure using open source or other solutions to aid various critical applications, such as analytic, reporting, AI/ML apps. Additionally, you will be deploying cloud stacks supporting big data and AI/ML platforms, locating production errors and issues. You are able to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams. You will interact with many other teams to lead and deliver best-in-class products in an exciting fast-paced environment. Dynamic, inquisitive people and inspiring, innovative technologies are the norm here. Will you join us in crafting solutions that do not yet exist?
Education & Experience
BS in Computer Science or related field or equivalent.
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. Learn more about your EEO rights as an applicant (Opens in a new window) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .
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