Data Quality Consultant

About the role

The Data Quality Consultant will lead the design, implementation and continuous improvement of data quality practices across the enterprise. You will work closely with data owners, stewards and technical teams to ensure data is accurate, complete, consistent and reliable, supporting key business decisions.

Key responsibilities

• Design, implement, and maintain enterprise data quality controls, standards and monitoring processes.
• Perform data profiling, validation, quality assessments and root‑cause analysis to identify issues.
• Develop and implement data quality rules, scorecards, KPIs and monitoring dashboards.
• Support data cleansing, remediation and issue‑resolution activities across business and technology domains.
• Conduct data quality assessments and provide recommendations for improvement initiatives.
• Collaborate with business users, data owners, stewards and technical teams to resolve data quality issues.
• Configure and administer data quality tools and platforms to meet enterprise requirements.
• Monitor data quality metrics and ensure compliance with established standards and policies.
• Produce reports, dashboards and analyses related to data quality performance and compliance.
• Support metadata management, data lineage and broader data governance initiatives.

Required profile

• Bachelor's degree in Computer Science, Information Systems, Data Management, IT, Engineering or a related discipline.
• CDMP Data Quality (DQ) certification is a plus.
• At least five years of experience in data quality management, data governance or related fields.

Required skills

• Data Quality Metrics KPIs and Reporting
• Data Governance Frameworks and Standards
• Data Quality Monitoring and Scorecards
• Data Quality Management
• Data Quality Tool Configuration Development and Administration
• Metadata Management and Data Lineage Awareness
• Data Validation and Data Verification
• Data Quality Rules Development and Implementation
• Master Data and Reference Data Quality Management
• Data Cleansing and Remediation
• Root Cause Analysis and Issue Resolution
• Technical implementation of Data Quality controls and governance processes
• SQL and Data Analysis
• Data Profiling and Data Assessment