AI and Data Engineer, Google Cloud

## About the Role Google Cloud is hiring an AI and Data Engineer to help customers and engineering teams build AI-ready data foundations. The role combines data engineering, distributed data processing, AI infrastructure, and client-facing technical problem solving. You will help design foundational data layers and prepare enterprise data for modern AI and agentic use cases. ## Responsibilities - Design and implement foundational data layers for AI and analytics workloads. - Build and optimize large-scale data pipelines using distributed data processing technologies. - Design data policies and establish reliable sources of truth across data domains. - Prepare and transform enterprise data for AI and agent-based applications. - Build data pipelines supporting AI agents, vector databases, feature stores, and retrieval-augmented generation workloads. - Optimize data structures and datasets for retrieval and AI applications. - Troubleshoot complex technical issues and work directly with customers and engineering teams. - Develop solutions using Google Cloud data technologies such as BigQuery and Dataflow. - Consider data privacy, compliance, access control, and governance when designing data infrastructure. - Collaborate with Product Managers, Engineers, and Google Cloud customer teams to influence technical solutions and product direction. ## Requirements - Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience. - 5+ years of experience working with data-processing software such as Hadoop, Spark, Pig, or Hive. - Strong understanding of data structures, algorithms, and distributed data processing. - Experience managing client-facing technical projects and troubleshooting complex technical issues. - Strong data engineering and data infrastructure fundamentals. - Experience with data pipelines, data modeling, and large-scale data platforms. - Strong communication and stakeholder-management skills. ## Nice to Have - Experience building data pipelines specifically for AI agents. - Experience with vector databases, vector embeddings, or feature stores. - Knowledge of Google Cloud services such as BigQuery, Dataflow, Pub/Sub, and Vertex AI. - Experience with data privacy, compliance, and governance in large organizations. - Understanding of RAG and modern Generative AI data architectures. - Experience designing multi-tenant or highly scalable data platforms.