Join a pioneering team as a Software Engineering Manager, leading the Enterprise Data Platform and Governance initiative. This role is crucial for shaping how data is managed, engineered, and leveraged through advanced analytics. You will guide the technical direction and manage a team of engineers, contributing to the strategic vision of Google's data infrastructure. This is an opportunity to influence the development of AI-ready data products and drive large-scale projects that empower business and engineering partners.

As a manager, you'll possess both deep technical expertise and strong leadership capabilities. You will oversee multiple teams, manage significant budgets, and ensure the successful deployment of complex, large-scale projects. Your work will directly contribute to building world-leading business solutions that enhance Google's ability to serve users effectively, focusing on areas like AI, distributed computing, and large-scale system design.

Lead strategic programs focused on developing Artificial Intelligence (AI)-ready data products and enterprise data infrastructure to support large-scale Agentic use cases.

Champion the design and implementation of semantic architectures, embedding critical business context into the data layer to enable sophisticated AI agents.

Influence the Connected Data strategy, promoting consistent and secure data assets based on canonical entity schemas for advanced enterprise insights.

Create and maintain logical and physical database designs, prioritizing property-graph models and flexible architectures for complex semantic layers.

Uphold data integrity through strict security and governance procedures, ensuring the highest standards of confidentiality and data security.

A Bachelor's degree or equivalent practical experience is required.

Candidates should have at least 8 years of software development experience, with proficiency in languages such as Python, C, C++, Java, or JavaScript.

Proven experience of 3 years in people management, including project oversight, coupled with 2 years of technical leadership and team supervision.

Demonstrated ability in designing and implementing efficient, large-scale distributed systems throughout their full project lifecycle.

Experience with advanced AI/ML analytics solutions, machine learning, and statistical analytics is preferred.

Familiarity with implementing and integrating third-party applications within various business domains like Finance, Supply Chain, HR, and Marketing is advantageous.

Expertise in conceptual, logical, and physical data modeling, as well as data architecture, is highly desirable.