Senior People Analytics Lead

GEICO GEICO · Insurance · Richardson, TX +2

Senior People Data & Analytics Lead to manage and leverage people data from Workday and other HR systems to provide business insights. Responsibilities include creating and maintaining a data dictionary, applying data engineering practices for reliable pipelines and data models, and improving automation and observability.

What you'd actually do

  1. Understand and document People data in Workday and other HR systems, including key entities, relationships, and end-to-end data flows.
  2. Create and maintain a People data dictionary (business definitions, calculations, lineage, and system-of-record guidance) that HR can use for reporting and integrations.
  3. Model data for analytics (data warehouse/OLAP concepts, dimensional modeling) and enable self-service BI and reporting (Power BI, Superset or similar).
  4. Proactively anticipates data and reporting needs and updates reporting assets regularly to reflect evolving business priorities and stakeholder requirements.
  5. Serves as a consultant for the organization’s data needs, advising teams on how to translate business questions into actionable data and reporting solutions.

Skills

Required

  • Workday
  • HR data
  • data dictionary
  • data modeling
  • data engineering
  • reporting
  • BI tools
  • data governance
  • data privacy

Nice to have

  • Workday reporting
  • Workday integrations
  • Power BI
  • identity and access management
  • change management

What the JD emphasized

  • Experience building and maintaining an HR-facing data dictionary, metric catalog, or semantic layer used for reporting and downstream consumption.
  • Experience working with People/HR data (e.g., Workday) and understanding core HR concepts such as worker lifecycle events, job/position structures, org hierarchies, compensation, benefits, time, and security.
  • Hands-on experience leveraging HR data for insights: definitions, ownership, system of record, lineage, and known data quality considerations.
  • Knowledge of data privacy and access principles for employee data (e.g., least privilege, sensitive data handling) and ability to work within governance standards.
  • Familiarity with data governance practices (stewardship, approvals, data quality monitoring, and auditability) for sensitive employee data.