Senior Workforce Intelligence Analyst

Join our team as a Senior Workforce Intelligence Analyst, where you will drive the adoption of an AI-powered self-service analytics suite for the People team. You will own the configuration and management of Visier, build and extend content, manage data quality, and act as an embedded partner to various HR functions. You will also be responsible for raising the data literacy of the HR function and delivering the self-service analytics roadmap.

• Conduire l'adoption de l'analyse autonome au sein de l'équipe People en utilisant Visier et Claude.
• Gérer l'intégration entre notre plateforme de données et Visier, en collaborant avec l'ingénierie des données sur les modèles en amont.
• Assurer la qualité des données, définir les contrôles, trier les échecs et conduire les corrections.

• Hands-on Visier experience: You must have gone through at least one implementation or meaningful capability expansion (deploying Visier or standing up new data subjects in an existing tenant)
• Ability to work independently, prioritize concurrent workstreams, and handle sensitive data with total discretion
• Demonstrated experience enabling others, whether through training, documentation, or converting a reporting backlog into self-service
• Fluency in the HR domain: you deeply understand recruiting, compensation, performance, and org structure, and know how underlying systems actually record this data
• A pragmatic approach to data governance. You know how to balance standardized dashboards for large audiences and enable exploration for your clients
• 4+ years in people analytics, HR technology, or a closely related role
• Strong SQL skills and comfort working directly in a cloud data warehouse
• Experience in high-growth or infrastructure environments where change is constant and part of the fun
• Experience using other BI platforms (Power BI, Tableau, Sigma) alongside Visier
• Experience with our specific stack: Rippling, Workday, Ashby, Lattice, TeamOhana, BigQuery
• Understanding of how to expose warehouse data to LLMs or agentic interfaces (semantic layers, MCP)
• Analytics Engineering capability: Experience with dbt, version control, CI/CD, and dimensional modeling. If you can own the transformation layer and not just the presentation layer