Senior Data Governance Analyst

Kforce's client, a large, stable enterprise organization in Draper, UT, is seeking a Senior Data Governance Analyst to lead initiatives that ensure the accuracy, consistency, and integrity of enterprise master data across systems. This role plays a key part in defining and enforcing data governance standards, improving data quality, and supporting strategic reporting and analytics initiatives. The ideal candidate brings deep experience in data governance and master data management, strong analytical skills, and the ability to influence data-driven decision-making across cross-functional teams. This position also provides mentorship and leadership support to junior analysts. Responsibilities:

• Lead the design, implementation, and execution of data governance controls, tools, and reporting dashboards
• Identify, resolve, and prevent complex data integrity issues through data cleansing and remediation initiatives
• Provide strategic recommendations for master data design, governance policies, and process improvements
• Oversee data validation, stewardship, and reporting cycles to ensure accuracy and consistency across enterprise systems
• Mentor and guide junior analysts, supporting enterprise-wide data governance adoption and training
• Partner with cross-functional teams to support data quality, compliance, and reporting initiatives
• Support strategic analytics and reporting efforts by ensuring trusted, well-governed data assets
• Bachelor's or Master's degree in IT, Business Analytics, or a related field
• 5+ years of experience in data governance, data quality, or enterprise data management
• Proven experience managing master data and driving data quality initiatives in an enterprise environment
• Advanced proficiency in SQL and Power BI
• Experience working with enterprise systems such as SAP, Snowflake, and Dayforce
• Experience in cloud data environments and metadata management preferred
• Analytical problem-solving and attention to detail

• Data governance and master data management
• Data quality analysis and remediation
• Stakeholder collaboration and influence
• Documentation, standards development, and process improvement
• Mentorship and knowledge sharing

• Enterprise data and analytics organization
• Highly collaborative, cross-functional setting
• Emphasis on data accuracy, governance, and long-term data integrity