People Analytics Analyst

Intuitive•Peachtree Corners, GA

About The Position

The People Analytics Analyst owns end-to-end analytics products, from data sources through apps, dashboards, and reports, and serves as a subject matter expert for HCM data and reporting. The role turns data from systems such as the applicant tracking system, Workday, Anaplan, Qualtrics, Snowflake, and the enterprise data warehouse into trusted, accessible insights that help HR and business leaders make decisions. The analyst works independently with little day-to-day instruction, resolves moderate to complex problems, and supports less experienced colleagues. The role partners with HR Operations, People Services, Talent Acquisition leadership, HR Business Partner leaders, Finance, HRIS, IT, and Enterprise Analytics. It develops and maintains analytics products, integrates and governs data, communicates findings, improves recurring reporting, and applies sound statistical methods and emerging tools, including AI and advanced analytics. This position may be filled at a different job level depending on business need and the selected candidate’s experience, knowledge, and skills. Compensation is based primarily on the level at which the role is filled and the candidate’s qualifications. Intuitive notes that vaccination proof may be required for some roles, and that certain roles may be subject to U.S. export controls.

Requirements

Bachelor’s degree and 5 years of related experience in data analytics and visualization, business intelligence, or analytical consulting; or a Master’s degree and 3 years of experience; or equivalent experience.
Ability to use data, analytics, and business knowledge to solve moderate to complex business problems.
Hands-on experience with Tableau or an equivalent data visualization tool.
Strong SQL skills against a relational database.
Experience with AI-integrated workflows, such as Claude/Devin/Cortex → Git → Products.
Experience combining data from multiple systems into reliable reporting, with attention to data quality.
Strong written and verbal communication skills, including simplifying complex information for different audiences and influencing stakeholders.
Experience delivering a first working version, gathering real-world feedback, and iterating with a continuous-improvement mindset.

Nice To Haves

Master’s degree.
HR or talent analytics experience.
Familiarity with Workday reporting, Prism, or integrations and ATS data.
Experience with Snowflake or a cloud data warehouse.
Experience with R or Python.
Experience with project management tools.
Experience with AI or automation tools applied to analytics.

Responsibilities

Design, build, and maintain analytics apps, dashboards, and reports.
Partner consultatively with HR Operations, People Services, Talent Acquisition leadership, HR Business Partner leaders, and Finance to understand business questions, scope requirements, and recommend metrics, methods, and analyses.
Identify, analyze, and interpret trends supporting workforce and talent decisions, and recommend process improvements based on data patterns such as bottlenecks and conversion rates.
Translate findings into clear, visually effective stories and present or demonstrate them to HR, Talent Acquisition, and business leadership.
Develop templates and automation, including AI-assisted tools, to standardize recurring reporting and reduce maintenance effort.
Query, model, and combine data from Workday, ATS, Anaplan, Qualtrics, Snowflake, and the enterprise data warehouse for regular and ad hoc reporting.
Work with HRIS, IT, and Enterprise Analytics to design and support integrations and data models and identify data-management improvements.
Define and document standard metric and data definitions, and conduct recurring data-quality audits with remediation plans shared with partners.
Monitor dashboard performance and data integrity, test and QA changes, and resolve issues quickly.
Participate in developing and implementing data governance with key stakeholders.
Manage projects and priorities across multiple stakeholders, adjusting as business needs change.
Coach and support less experienced team members and partners in using data and tools effectively.
Apply sound statistical understanding to ensure accurate insights and pilot predictive approaches where useful.
Continue learning tools and methods, including AI and advanced analytics, and bring improvements to the team.