Business Intelligence Analyst, Product Data Warehouse

Google•Boulder, CO

2d•$116,000 - $166,000

About The Position

The Go-to-Market Product Data Warehouse (PDW) team supports Google Ads reporting by tracking and publishing product adoption metrics, supporting data needs for product launches and betas, and preparing analyses that inform sales and product decisions about ad features. The role is on 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 will deliver end-to-end business intelligence solutions supporting Google's commercial measurement strategy and Go-to-Market execution. You will work with Global Product Solutions to identify important ad features and goals and define how success is measured; collaborate with Ads Product Management and Engineering to understand backend systems and develop actionable KPIs; and work with regional go-to-market teams to understand seller needs. You will build and own data pipelines, structured tables, and user-friendly dashboards used by thousands of sellers daily.

Requirements

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, such as Looker, Tableau, Power BI, Qlik, or similar technologies.

Nice To Haves

Experience with data warehousing or data modeling concepts.
Experience with big data technologies such as Hadoop, Spark, Python, or R.
Experience translating business requirements into BI solutions.
Experience explaining technical analysis to stakeholders.

Responsibilities

Partner with Go-to-Market teams to understand Ads product and 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.
Translate analyses into compelling insights and communicate the implications to commercial leaders through clear verbal and written communications.
Create intuitive dashboards, reports, and tools that enable self-service analytics across thousands of stakeholders.
Prioritize requests and use a portfolio of solutions, from ad hoc analyses to scalable pipelines, balancing short-term needs with long-term scalability.
Use AI to accelerate development cycles while ensuring data and pipelines are fully tested and validated.