Data Platforms Engineer - Manufacturing Systems and Infrastructure

Apple Inc.•Cupertino, CA

48d

About The Position

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple's Manufacturing Systems and Infrastructure (MSI) team is responsible for capturing, consolidating and tracking all manufacturing data for Apple's products and modules worldwide. We are a multi-functional team, tackling challenging software engineering problems across a broad range of Apple manufacturing services. You'll be leading innovation by exploring, investigating, recommending, benchmarking and implementing full stack technologies for the platform. This data is used throughout the company and the product's lifecycle: from the very beginning, to validate that units being built are fully tested and of high quality before leaving the factory, all of the way through to warranty support for customers. Apple's MSI team is seeking a Software Engineer with a strong passion for building innovative platform solutions, specializing in GenAI data frameworks, and a deep appreciation for delivering exceptional user experiences.In this role, you will be responsible for defining and developing scalable, cloud-native data platform solutions and frameworks, with a focus on managing both structured and unstructured data to enable generative AI-powered applications within Apple Product Operations. You will be responsible for architecting, developing, and maintaining large-scale systems, pipelines, storage solutions, and data quality services. You will collaborate with diverse cross-functional partners, including business teams from product operations, HW engineering, machine learning engineers, data scientists, application developers and product managers. You will have the opportunity to learn and work on the latest technologies, lead POCs to demonstrate new ideas and influence the future direction of our technology stack and solutions development

Requirements

Strong software development, problem-solving, and debugging skills, with proficiency in one or more of the following languages: Python, Java, Scala, or Go
Deep expertise in Big Data technologies such as Apache Spark, Kafka, Hive, Iceberg, Trino, Airflow, or Flink
Experience building cloud-native platforms using containerization technologies (Kubernetes, Docker, Helm) and hands-on knowledge of AWS, GCP, or Azure
Proven ability to manage data at scale, including pipeline optimization, validations, and data quality measures
Experience working with Generative AI models and implementing robust data strategies to support LLM-based applications
Skilled at quickly analyzing and simplifying complex problems into clear, practical solutions
Self-directed, motivated, and detail-oriented, with the ability to design effective solutions and perform thorough production issue analysis
Ability to thrive in cross-functional teams on high-profile, critical projects
Proactive in exploring alternate technologies and innovative approaches to problem-solving
Strong people management capabilities and excellent collaboration skills across teamsArray

Nice To Haves

Exposure to front-end/UI technologies is a plus

Responsibilities

defining and developing scalable, cloud-native data platform solutions and frameworks
managing both structured and unstructured data to enable generative AI-powered applications
architecting, developing, and maintaining large-scale systems, pipelines, storage solutions, and data quality services
collaborating with diverse cross-functional partners
lead POCs to demonstrate new ideas and influence the future direction of our technology stack and solutions development

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