Data Modeling & Data Governance Senior Consultant - Global Employer Services Technology

This role focuses on designing, standardizing, and governing enterprise data assets, including developing conceptual, logical, and physical data models and establishing data governance frameworks. It emphasizes data quality, usability, and compliance within a professional services firm.

What you'd actually do

  1. Develop and maintain conceptual, logical, and physical data models for enterprise and domain initiatives.
  2. Partner with business stakeholders, data architects and analysts to translate business requirements into scalable data models and standards.
  3. Advance the enterprise conceptual and canonical data models to improve consistency across systems, integrations, and reporting.
  4. Ensure data models align with enterprise architecture standards, integration patterns, and reporting needs.
  5. Define and document business terms, data definitions, data standards, and critical data elements.

Skills

Required

  • data governance
  • data modeling
  • data standards
  • metadata
  • data quality
  • conceptual, logical, and physical data models
  • entity-relationship
  • star/snowflake schemas
  • 3rd normal form
  • data modeling tools (Erwin, Lucid or Visio)
  • business glossaries
  • critical data elements
  • catalog/metadata practices
  • data ownership
  • stewardship
  • metadata
  • lineage
  • data quality
  • privacy
  • retention
  • access controls
  • leading workstreams for data management engagements
  • facilitating cross-functional workshops

Nice to have

  • metadata management
  • lineage
  • stewardship
  • data quality
  • policy management
  • metadata management and data lineage tools
  • semantic layers for analytics and agentic AI use cases
  • Data Management
  • Data Engineering
  • security
  • privacy
  • compliance considerations in data environments
  • defining and implementing data products within data catalog and marketplace
  • cloud-based data lakes and warehouse technologies (Apache Iceberg, Databricks, Redshift, Snowflake)
  • influencing cross-functional stakeholders
  • leading enterprise-wide initiatives
  • lead, motivate, and develop a team of data professionals
  • analytical and problem-solving skills

What the JD emphasized

  • experience leading solution and data architecture in broadscale transformation programs
  • strategical data management and analytics / AI initiatives
  • drive the design, standardization, and governance of enterprise data assets
  • define and operationalize data governance practices
  • compliance with regulatory, security, and privacy requirements