About The Position

At Apple, we work every day to create products that enrich people's lives. The Apple Ads group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. The Apple Ads Data Governance team develops privacy-centric advertising solutions that leverage advanced data engineering and machine learning technologies at massive scale. The Data Governance Engineer role involves collaborating with cross-functional teams to implement critical privacy safeguards, and data management controls. At Apple Ads, we are building the next generation of privacy-focused advertising capabilities. In the Data Governance team, we work at the cutting edge of data engineering, machine learning, and privacy at Apple's scale. We are constantly developing data and privacy management products to provide amazing user experiences and to drive value for developers and partners.

Requirements

  • Expertise in open source data analytics and governance platforms: architecture, deployment, and performance tuning of Datahub, Apache Spark, Flink, Hive, Hadoop/HDFS, and Iceberg Rest Catalog.
  • Experience building multi-agent AI systems: proficiency with LangChain, LangGraph, or AutoGen frameworks; strong prompt engineering and LLM integration skills; ability to design event-driven architectures for autonomous workflows.
  • Skills in integration and communication layers: implement MCP servers and APIs using Python, REST/GraphQL, and message queuing (e.g. Kafka, RabbitMQ); experience with modern data platforms including Snowflake, Databricks, and vector databases.
  • MLOps and observability capabilities: deploy containerized AI systems with comprehensive monitoring; track experiments using MLflow or Weights & Biases; implement distributed tracing for agent workflows and model performance.

Responsibilities

  • Support data governance objectives by delivering on Apple's privacy commitments to customers.
  • Collaborate with engineering, product, privacy, and reliability organizations.
  • Implement data access, use, protection, minimization, retention, and other data governance execution areas.
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