Join our Enterprise Data Platform and Governance Team as a Software Engineering Manager. You'll lead initiatives in Data Architecture, Data Engineering, and Analytics technologies, empowering engineers and business partners. This role is crucial for delivering innovative data management and investigative solutions across Google, driving high-impact projects that shape the future of enterprise data.

As part of the Corp Eng organization, you will contribute to building world-leading business solutions that scale a more helpful Google for everyone. We provide end-to-end IT solutions, delivering the tools, platforms, and experiences that enable Googlers to create exceptional products and services.

Lead strategic programs focused on building AI-Ready Data products and establishing enterprise data infrastructure for large-scale Agentic use cases. Advocate for semantic architectures that embed business context into the data layer, enabling advanced AI agents. Influence the Connected Data strategy to ensure secure, consistent data assets with canonical entity schemas for richer enterprise insights. Develop and maintain logical and physical database designs, incorporating property-graph models and flexible data architectures for complex semantic layers. Uphold data integrity through strict security and governance procedures, maintaining the highest levels of data security and confidentiality.

This role requires a Bachelor's degree or equivalent practical experience, coupled with at least 8 years of software development expertise in languages like Python, C, C++, Java, or JavaScript.

Significant experience is needed in people management (3+ years) and technical leadership (2+ years), including project oversight and team supervision.

Demonstrated experience in designing and implementing efficient, large-scale distributed systems throughout the full project lifecycle is essential.

Preferred qualifications include experience with advanced AI/ML analytics, integrating third-party applications in various business domains (Finance, Supply Chain, HR, Marketing), and expertise in conceptual, logical, and physical data modeling and data architecture.