Data Governance Engineer - Data Governance Engineering

Data Governance Engineer - Data Governance Engineering

Austin, Texas, United States

Software and Services

Summary

Posted : Sep 23, 2025

Weekly Hours : 40

Role Number : 200622493-0157

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.

Description

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.

The team is seeking a Data Governance Engineer to support our data governance objectives. You will play a crucial role in delivering on Apple's privacy commitments to our customers. You will partner across our engineering, product, privacy and reliability organizations to deliver on data access, use, protection, minimization, retention, and other data governance execution areas.

Responsibilities

Design autonomous governance agents for petabyte-scale data pipelines (e.g. Kafka, Spark, Hadoop) ensuring compliance and quality across all processing stages

Build MCP integrations enabling automated policy enforcement, PII detection, and data quality validation across diverse storage and compute environments

Partner with engineers and PMs to develop intelligent monitoring that detects anomalies, generates compliance reports, and auto-remediates issues

Create reusable agent templates and workflows that adapt to changing regulations while maintaining performance and reducing manual compliance

Contribute to distributed agent ecosystem emphasizing reliability through self-healing mechanisms, automated failovers, and dynamic resource allocation for scalability

Minimum Qualifications

B.S. in Computer Science or related field with 4+ years of software development experience, including exposure to ML / AI applications

Production experience in Python or similar languages, with familiarity in data processing and API development

Understanding of distributed systems and cloud platforms, including basic ML model deployment

Experience with containerization (Docker), orchestration (Kubernetes), and infrastructure as code (e.g. Terraform, CloudFormation)

Proficiency in CI / CD pipelines and DevOps practices using Git, GitHub Actions / Jenkins / GitLab CI, with experience in automated testing and deployment workflows

Familiarity with observability and monitoring tools (e.g. Prometheus, Grafana, DataDog) and logging frameworks for production systems

Basic knowledge of machine learning concepts and MLOps, including data pipelines, model versioning, and experiment tracking tools

Preferred Qualifications

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

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 () .

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 () .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program () .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

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