Staff Software Engineer, Enterprise Data Platform and Governance
Google · United States · Posted 2026-08-28
Job description
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).