Data Governance Analyst: Drive Data Quality & Stewardship

Continental Properties; Menomonee Falls (WI); On-site; USD 67,000 - 84,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) with company match

Paid parental leave

Life and disability insurance

Job summary

Continental Properties is seeking a Data Governance Analyst to join the Data Management team at the home office in Menomonee Falls, WI. You will help keep data governed and trustworthy by facilitating stewardship decisions, monitoring data quality, and maintaining the catalog, glossary, and lineage that enable the business to confidently find and use its data.

This hands-on role supports the AI-driven data access and self-service analytics expansion, working cross-functionally with engineering,

Qualifications

• Bachelor's degree preferred, or equivalent practical experience.
• 2-4 years in data governance, data management, BI, or related analytical role.
• Hands-on experience with data cataloging, business glossary/definitions, data lineage, or data stewardship.

Responsibilities

• Facilitate domain-based data stewardship model and support steward decisions.
• Monitor data quality and governance health, triaging exceptions and trends.
• Maintain and expand data catalog with ownership, descriptions, and classifications.
• Build and curate the business glossary with stakeholders; standardize new terms.
• Document and validate data lineage across ingestion, transformation, and reporting.

Skills

Data governance

Data management

Communication skills

Cross-functional collaboration

Education

Bachelor's degree

Tools

Relational databases

Data cataloging tools

Data lineage tooling

Job description

Continental Properties is seeking a Data Governance Analyst to join the Data Management team at the home office in Menomonee Falls, WI. You will help keep data governed and trustworthy by facilitating stewardship decisions, monitoring data quality, and maintaining the catalog, glossary, and lineage that enable the business to confidently find and use its data.

This hands-on role supports the AI-driven data access and self-service analytics expansion, working cross-functionally with engineering,