People Data Analyst

Join our team as a People Data Analyst, where you'll build a reliable data foundation, turn data into actionable insights, connect people data to business objectives, measure the success of our initiatives, and support AI-driven projects. Enjoy benefits such as extended healthcare, flexible paid time off, team activities, and a learning budget.

Responsibilities

• Construire une base de données fiable et de confiance, en veillant à la qualité des données et en déplaçant les rapports vers ThoughtSpot.
• Analyser les données pour identifier les domaines d'amélioration, proposer des idées basées sur les résultats et fournir des recommandations aux dirigeants.
• Connecter les données des employés aux objectifs commerciaux, en collaborant avec le département des finances pour améliorer la planification des effectifs.
• Strong SQL skills and experience with modern cloud data platforms, such as Snowflake (preferred), BigQuery, or Databricks. You're comfortable working with large datasets and understanding how data moves from source systems into analytical models

Requirements

• Comfort with Git-based development workflows. Version control, branches, pull or merge requests, code review, and collaborative development are a normal part of how you work
• Strong experience with modern BI and analytics platforms, such as ThoughtSpot (preferred), Looker, or Omni. You've built dashboards and analytical experiences that people genuinely use, and you understand how the BI layer connects to the underlying data models and sources
• Hands-on experience with dbt or similar analytics engineering practices. You know how to build maintainable transformation pipelines, structure models, test and document data, and manage dependencies between datasets
• 3+ years of experience as a Data Analyst, taking messy raw data through to a clear insight and a recommendation. Experience embedded in a business function is even better
• Experience working with sensitive data and analytics access controls. You understand concepts such as role-based access, row-level security, column-level security, data masking, and least-privilege access, and can apply them pragmatically when working with sensitive People data