Product Manager, Data Infrastructure, Analytics and Insights

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in product management or related technical role. 3 years of product management or related experience in data infrastructure, database systems, data lakes/warehouses, or OLAP for AI/ML workloads. 2 years of experience taking technical products from conception to launch. Preferred qualifications: Master's degree in a technology or business related field. 3 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting). 2 years of experience in software development or engineering. 2 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders. 1 year of experience in technical leadership. Experience in life-cycle data roll-outs at scale, promoting product excellence and collaboration. 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 Data Analytics and Insights team builds the storage, processing, query, and visualization infrastructure that powers business decisions throughout Google, transforming, optimizing, and aggregating data for all major products. Taken as a whole, this infrastructure is the foundation for the data powered decisioning and ML for the consumer products at Google. In this role, you will oversee how we use our storage infrastructure to deliver data insights and ML-ready data assets across a multitude of areas within Google. You will help product teams spend more time acting on insights and building models rather than on managing their storage infrastructure, thus improving productivity as well as our ability to act using the best available data as our guide, shaping how Google uses data for analysis, machine learning, and AI. The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities: Partner with engineering leadership to identify needs and best practices in order to build and bring to market innovative storage products and solutions that drive significant impact for Google. Be responsible for building goals and strategy, and driving execution for Core Data Storage products. Understand the landscape of the scalable storage products, their ecosystem of processing and querying systems while satisfying key business cases to safely and efficiently ingest and manage data. Drive and increase adoption of the storage portfolio by supporting new Google-wide ML use-cases. Work with cross-product teams to build integrated solutions based on the product portfolio, simplifying data management and governance for our customers.

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