Data Governance Engineer Data Governance Engineering
Data Governance Engineer Data Governance Engineering
Posted on :
26-09-2025
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1 Vacancy
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Job Description
At Apple Ads we are building the next generation of privacy-focused advertising the Data Governance team we work at the cutting edge of data engineering machine learning and privacy at Apples 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 Apples 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.
- 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
- 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
Employment Type
Full-Time
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