Business Intelligence Analyst, Product Data Warehouse

Business Intelligence Analyst, Product Data Warehouse Share Business Intelligence Analyst, Product Data Warehouse _corporate_fare_ Google _place_ Atlanta, GA, USA; Boulder, CO, USA; +7 more; +6 more **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Business Intelligence Analyst, Product Data Warehouse _info_outline_ XThe application window will be open until at least November 3, 2026. This opportunity will remain online based on business needs which may be before or after the specified date. This role may also be located in our Playa Vista, CA campus. Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Mountain View, CA, USA; Los Angeles, CA, USA; San Bruno, CA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA** . **Minimum qualifications:** + Bachelor’s degree or equivalent practical experience. + 4 years of experience in Business Intelligence or Data Analytics. + 4 years of experience in SQL and Data Visualization (e.g., Looker, Tableau, Power BI, Qlik, or similar technologies). **Preferred qualifications:** + Experience with data warehousing or data modeling concepts. + Experience with big data technologies (e.g., Hadoop, Spark, Python, or R). + Experience with translating business requirements to BI solutions. + Experience with explaining technical analysis to stakeholders. **About the job** The Go-to-Market Product Data Warehouse (PDW) team supports Google's Ads data reporting needs - tracking and publishing key product adoption metrics, supporting data needs for product launches and betas, and preparing analyses that inform sales and product decisions on ad features. This role sits within the PDW XPS (Cross-Product Solutions) team, and owns product data and reporting related to Audiences, Google Marketing Platform (GMP), and Privacy and Responsibility. As a Business Intelligence Analyst on the PDW Measurement team, you'll deliver end-to-end business intelligence solutions that power Google’s commercial measurement strategy and Go-to-Market (GTM) execution. You'll work with Global Product Solutions (GPS) to identify key ad features and goals and define what "good" looks like and how it's measured: with Ads PM and Engingeering to understand the backend systems that power our ads and turn them into actionable KPIs, and with regional go-to-market teams to learn what matters to sellers. You'll build and own the end-to-end data pipelines, structured tables, and user-friendly dashboards that serve thousands of sellers daily. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $116000 - $166000 (USD) + 15% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) . **Responsibilities** + Partner with Go-to-Market (GTM) teams to understand Ads product/feature priorities, translating questions into metrics and analyses. + Design robust data models and pipelines, partnering with Ads Engineering to integrate data from multiple sources and systems and translate analyses into compelling insights, communicating the "so what" to commercial leaders via clear verbal and written communications. + Create intuitive dashboards, reports, and tools to enable self-service analytics across our thousands of stakeholders. + Prioritize across engaging requests, utilizing a portfolio of solutions (from ad hoc analyses to scalable pipelines) that balance short-term needs with long-term scalability. + Leverage AI to accelerate development cycles while ensuring all data and pipelines are fully tested and validated. 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