Data Engineer

Apple • Cupertino, CA

3h

About The Position

Apple's Media, Graphics, and Compute Technologies Group (MGC) is looking for a
talented and dedicated big data engineer to join our Data Engineering team. The
Data Engineering team within the MGC organization plays a critical role in
supporting data-driven analytics by providing data collection, warehousing, and
analytics at big data scale. Our team provides the infrastructure to power
numerous trend and operational dashboards as well as other ad-hoc use cases in
support of services like Apple TV, Apple Music, and FaceTime. We are leveraging
Generative AI and Machine Learning technologies to provide best-in-class data
analytics and monitoring. This role offers the opportunity to help design,
enhance, and develop our very-high-volume processing pipeline. You'll work with
talented engineers within our team as well as cross-functional teams in an agile
and dynamic environment that values engineering excellence, creativity, and
innovation, and you will be a key contributor to our next generation of
processing pipeline and data analytics platform.

DESCRIPTION

Our team leverages modern Data Engineering, Generative AI and Machine Learning
technologies to deliver actionable insights. You will be: • Collaborating with
data scientists across functional teams to define and enhance performance
metrics that provide valuable insights for stakeholders • Building and
maintaining: - Ingestion pipelines for real-time data processing - Real-time
applications driving operational monitoring - Batch ETL/ELT applications
populating our data warehouse • Applying Generative AI and Retrieval Augmented
Generation (RAG) techniques to enhance data analytics capabilities • Applying
Machine Learning technologies for anomaly detection

Requirements

• Bachelor's degree in Computer Science or equivalent professional experience
• Experience in building large scale distributed systems in Java/Python or similar languages
• Proficient in SQL
• Experience with data warehouse architectures and dimensional modeling
• Demonstrated ability to conduct performance analysis and troubleshoot large scale distributed systems
• Strong collaboration skills with ability to understand complex architectures and work effectively across teams
• Hands-on experience with Docker and Kubernetes

Nice To Haves

• Production experience with Apache Kafka, Spark, or Flink
• Working knowledge of Trino or similar distributed query engines
• Experience building multi-agent AI systems or agentic workflows
• Familiarity with Retrieval Augmented Generation (RAG) techniques working in conjunction with LLMs
• Experience with creating and consuming Model Context Protocol (MCP) services

Responsibilities

• Collaborating with data scientists across functional teams to define and enhance performance metrics that provide valuable insights for stakeholders
• Building and maintaining ingestion pipelines for real-time data processing
• Building and maintaining real-time applications driving operational monitoring
• Building and maintaining batch ETL/ELT applications populating our data warehouse
• Applying Generative AI and Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities
• Applying Machine Learning technologies for anomaly detection

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level