Join a forward-thinking team as a Software Engineering Manager, focusing on Enterprise Data Platform and Governance. This role is pivotal in shaping Google's data architecture, engineering, and analytics technologies. You'll empower engineering and business partners, driving high-impact projects for critical corporate functions and Google-wide initiatives.

Be at the forefront of building AI-ready data products and enterprise data infrastructure. Your work will enable large-scale agentic use cases and influence the connected data strategy to deliver richer enterprise insights. This is an opportunity to lead a team that's shaping the future of data at Google.

Lead strategic programs to develop AI-ready data products and robust enterprise data infrastructure, particularly for large-scale agentic use cases. Advocate for and implement semantic architectures that embed crucial business context into the data layer. Influence the connected data strategy to ensure secure, consistent data assets based on canonical entity schemas, facilitating higher-level enterprise insights.

Create and maintain comprehensive logical and physical database designs, emphasizing property-graph models and flexible data architectures. Uphold data integrity by establishing strict security and governance procedures, ensuring the highest levels of confidentiality and data security.

We seek a candidate with a Bachelor’s degree or equivalent practical experience, coupled with at least 8 years of software development experience in languages like Python, C++, Java, or JavaScript. A minimum of 3 years in a people management role, including project oversight, and 2 years in a technical leadership or supervision capacity are essential.

Demonstrated experience in designing and implementing efficient, large-scale distributed systems throughout their entire project lifecycle is required. Preferred qualifications include experience with advanced AI/ML analytics, integrating third-party applications (Finance, Supply Chain, HR, Marketing), and expertise in conceptual, logical, and physical data modeling and data architecture.