Product Manager, Geo Auto Data Platform

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in product management or a related technical role. 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.). Experience with advanced driver‑assistance systems or autonomous driving features. Experience integrating generative AI tools or LLM interfaces into workflows. Preferred qualifications: Master’s or PhD degree in a technical field (e.g., GIS, Geomatics, Computer Science, Spatial Engineering). Deep domain expertise in ADAS/AD features and how these are supported by map data systems and standards (e.g., electronic horizon, ADASIS, NDS, HD maps, sensor fusion). Experience launching ADAS features into series production, ideally with global OEM customers. Technical background in map compilation, geospatial databases, and data quality validation methodologies for the automotive/ADAS domain. Proven ability to influence without authority in a highly matrixed, multi‑site environment. About the job: At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day. In this role, you will work cross‑functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development. One of the many reasons Google consistently brings innovative, world‑changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users. The Geo Auto Data Platform team is responsible for building the data foundation and platforms that power Google’s in‑vehicle automotive offerings. Our platform supports: enhanced, deeply integrated in‑vehicle turn‑by‑turn navigation and next‑gen visualizations powered by lane‑level positioning. Map data services supporting advanced driver‑assistance systems (ADAS) and autonomous driving (AD) to make roads safer, drives more comfortable, and lower carbon emissions and autonomous driving (L2++ and beyond) capabilities. In this role, you will have deep expertise with AD/ADAS features and with how map data supports such features. You will be ensuring our software, tooling, map data, and supporting services meet the rigorous safety, freshness, and accuracy standards required by AD/ADAS features. The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives. The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world. Individual pay is determined by factors including job‑related skills, experience, and relevant education or training. US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities: Manage and evolve the relationship with our upstream internal map data partners. This involves driving, reviewing, and approving ADAS‑specific map attribute schemas and documenting, establishing and enforcing cross‑functional governance to prevent fragmentation across divergent (non‑ADAS) use cases. Define, monitor, and defend data quality (accuracy and freshness) service level agreements (SLAs). Partner with engineering to prioritize automated validation loops. Translate downstream ADAS/AD feature mechanics to baseline software and data quality requirements; educate and advocate use cases with upstream data teams. Manage the ADAS country tiering model. Prioritize, negotiate, and drive the expansion of key ADAS attributes into new regions and deeper road categories across internal teams. Maintain open communication channels with original equipment manufacturer (OEM) partners to ensure our core roadmaps remain user‑ and partner‑focused. #J-18808-Ljbffr Socket.dev