Sr. People Data Analyst [Remote]

As a Senior People Data Analyst, you will measure and communicate organizational health metrics at an enterprise level. Our team focuses on generating insights that inform organizational goals such as increasing profitability, employee engagement, retention, and belonging. As we grow, you will help the People Analytics team advance by focusing on scaling our Workday analytics solutions. The ability to flex across consulting, process improvement, data visualization, data management, and stakeholder support will be important to your success. Responsibilities: Serve as the team's primary Workday reporting subject matter expert - owning the development of custom reports, calculated fields, dashboards, and scheduling. Enable cross-functional teams to access Workday data at an appropriate level of detail through scalable solutions. Manage the People Analytics service desk, triaging and fulfilling data requests from across the organization while looking for ways to handle them more efficiently through self-service, AI, or automation. Consult with department leaders to build and deliver data-driven recommendations. Conduct statistical analyses combining several sources of data to gain insights on human capital such as retention metrics. Ensure the proper maintenance and documentation of data sources, sensitive information, and processes. Requirements: Advanced proficiency in Workday Reporting, including: ○ Building and maintaining custom reports (advanced, matrix, composite), dashboards, and complex calculated fields. ○ Configuring report scheduling and developing Workday Drive items. ○ Self-service enablement and stakeholder testing. ○ Broad working knowledge of Workday business objects, with the curiosity and ability to learn new ones as needed ○ Experience with Prism analytics is a plus. Experience in Data Analytics, Industrial Organizational Psychology, HRIS management or other quantitative fields. Proficient at connecting and analyzing data in systems with related data sources primarily via SQL. Experience in data collection, cleaning, and management. Advanced proficiency building clear, auditable, easy-to-use spreadsheets in software such as Google Sheets. Skill in writing code that automates data tasks, such as Python or JavaScript. Understanding of statistical concepts (correlation, regression, T-test, ANOVA), research methods and experimental design. Skills in building and presenting data visualizations.