Data Steward

• Establish and maintain data quality standards, business rules, metadata definitions, and taxonomy frameworks across content domains
• Monitor dataset health and quality metrics to identify opportunities to improve accuracy, completeness, consistency, and timeliness
• Investigate recurring data-quality issues and conduct root cause analysis to develop preventive and scalable solutions
• Partner with operational teams to identify systemic issues and implement process improvements
• Develop and maintain quality dashboards, data dictionaries, governance documentation, and standard operating procedures
• Collaborate with product managers to translate operational insights into product requirements and enhancement opportunities
• Partner with engineering teams to define data-quality requirements and support automation initiatives
• Support complex customer escalations and investigations requiring strong domain and data expertise
• Drive cross-functional initiatives focused on content quality, operational efficiency, and scalability
• Promote standardization and best practices across content domains and workflows
• Identify opportunities to leverage AI and automation to improve quality and reduce manual effort
• Serve as a subject matter expert and trusted partner for data quality and governance initiatives
• Establish a unified quality framework across content domains
• Implement consistent metadata and taxonomy standards
• Build quality dashboards providing visibility into dataset health and quality
• Drive recurring quality issues to root-cause resolution across multiple domains
• Identify and pilot at least one AI or automation opportunity delivering measurable efficiency gains
• Establish scalable standards and practices improving data quality and operational efficiency

Data Steward – Quality Excellence

• Establish and maintain data quality standards, business rules, metadata definitions, and taxonomy frameworks across content domains
• Monitor dataset health and quality metrics to improve accuracy, completeness, consistency, and timeliness
• Investigate recurring data-quality issues and conduct root cause analysis
• Develop preventive and scalable solutions
• Partner with operational teams to identify systemic issues and implement process improvements
• Develop and maintain quality dashboards, data dictionaries, governance documentation, and standard operating procedures
• Collaborate with product managers to translate operational insights into product requirements and enhancement opportunities
• Partner with engineering teams to define data-quality requirements and support automation initiatives
• Support complex customer escalations and investigations
• Drive cross-functional initiatives focused on content quality, operational efficiency, and scalability
• Promote standardization and best practices across content domains and workflows
• Identify opportunities to leverage AI and automation to improve quality and reduce manual effort
• Serve as a subject matter expert and trusted partner for data quality and governance initiatives
• Establish a unified quality framework and consistent metadata and taxonomy standards
• Build quality dashboards providing visibility into dataset health
• Drive recurring quality issues to root-cause resolution
• Pilot at least one AI or automation opportunity with measurable efficiency gains