Business Intelligence Analyst, Product Data Warehouse

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 about
benefits at Google
.

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.

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.