Partner with the people analytics ecosystem to deliver research, guidance and people program insights (e.g., GRAD, Learning) at scale to critical user groups including Google’s leaders and people partners.
Automate, simplify, and maintain robust BI development workflows, proactively identifying opportunities to leverage GenAI tools (like Jetski) for rapid prototyping and agentic development.
Query, manipulate and analyze large data sets to distill insights from the data and connect disparate ideas into cohesive, well-grounded recommendations.
Partner cross-functionally (with POps engineering, data science, and BI) to define requirements and shape AI-ready data foundations including informing data mart design, contributing to semantic layers, authoring agent skills, and evaluating model outputs.
Minimum qualifications
Bachelor's degree in a quantitative discipline (e.g., Statistics, Math, Computer Science, Engineering) or equivalent practical experience.
5 years of experience with enterprise Business Intelligence (BI) suites (e.g., Looker, Power BI, Tableau, etc) and with enterprise datasets (e.g., workforce, finance, CRM/customer, or operations data).
Preferred qualifications
Experience applying statistical analysis, experimental design, or quantitative methods to solve scaled operations problems.
Experience collaborating on projects involving multiple teams, managing relationships with clients, and presenting to audiences.
Foundational understanding of Generative AI and data science concepts, particularly how they can be integrated into reporting workflows or leveraged via tools like Gemini/coding copilots.
Exceptional people management and communications skills.
Client service-oriented with an emphasis on creativity and diligence.
Bachelor's degree in a quantitative discipline (e.g., Statistics, Math, Computer Science, Engineering) or equivalent practical experience.
5 years of experience with enterprise Business Intelligence (BI) suites (e.g., Looker, Power BI, Tableau, etc) and with enterprise datasets (e.g., workforce, finance, CRM/customer, or operations data).