Staff Software Engineer, Enterprise Data Platform and Governance

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. As a Staff Software Engineer on the EDP&G team, you will serve as the principal technical architect and engineering leader anchoring embedded domain integration models. You will own the technical strategy, design, and execution required to bridge centralized enterprise data platforms with cross-domain business environments. In this role, you will define how Google builds high-integrity semantic engines and agentic endpoints that power autonomous AI workflows across the company. You will not only oversee implementation within critical domains, but you will also architect the core frameworks that allow domain-specific technical enhancements to scale back into the centralized Enterprise Data Platform. You are a technical visionary, a respected peer to group product leads, and a mentor to engineering teams navigating highly ambiguous, distributed, and data-intensive environments. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google . Define the technical roadmap, engineering standards, and integration patterns for embedded resources across multiple business domains to accelerate high-impact outcomes. Lead the technical design and execution of secure data onboarding workflows, knowledge graphs, and agentic endpoints capable of sustaining autonomous AI reasoning without human mitigation. Build technical frameworks that seamlessly harvest domain-specific data engineering successes and contribute them back as reusable, centralized features. Partner with Group Product Managers and Principal Business Strategy Analysts (BSAs) to solve complex, cross-domain data fragmentation hurdles, balancing localized velocity and business autonomy with rigid data substrate standards. Serve as the ultimate technical authority for privacy, compliance, trust and safety, and responsible AI practices across forward-deployed systems, ensuring infrastructure is secure by design. Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience programming in C++, Java, Python, Kotlin or Go. 5 years of experience testing, and launching software products. 3 years of experience with software design and architecture. Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 8 years of experience with data structures and algorithms. 3 years of experience in a technical leadership role leading project teams and setting technical direction. 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. Deep technical mastery of semantic modeling, knowledge graph construction, large-scale data pipeline engineering, and deploying production-grade AI/ML infrastructure (e.g., advanced Retrieval-Augmented Generation (RAG) frameworks, model evaluation pipelines, agentic orchestration). Bachelor's degree or equivalent practical experience. 8 years of experience programming in C++, Java, Python, Kotlin or Go. 5 years of experience testing, and launching software products. 3 years of experience with software design and architecture. Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.