AI and Data Engineer, Google Cloud

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses grow. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

The Central Tooling and Analytics team is the operational backbone of Google Cloud’s efficiency. We specialize in engineering high-impact tools and streamlined workflows designed to reduce manual toil and improve decision making. At the core of our tooling and analytics strategy, the Central Data Engineering team aims to provide high-quality signals required to power agentic workflows and AI-driven automation across the organization curating data across many critical pillars like programs, products and people.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
  
• 5 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
  
• Experience managing client-facing projects, troubleshooting technical issues, and working with engineering and sales services teams.

Preferred qualifications:

• Experience building data pipelines specifically for AI agents, vector databases, or feature stores.
• Experience managing data privacy and compliance in a highly regulated or large-scale corporate environment.
• Strong understanding of data infrastructure concepts and ability to layout policies for a foundational data layer.
• Familiarity with Google Cloud’s data stack (BigQuery, Dataflow, Pub/Sub, Vertex AI).
• Ability to translate executive-level business requirements into technical data architectures.