Data Quality Management:
Ensure high data quality by performing data analysis, profiling, and continuous monitoring to detect and resolve data quality issues promptly
Develop, maintain, and enforce data quality standards, policies, and procedures to support consistent and reliable data across the organization
Collaborate with stakeholders to define data quality metrics and targets, taking full ownership of KPI implementation, monitoring, and reporting across all relevant data domains
Data Governance:
Implement defined data governance framework with respect to Master Data, including processes, roles, and control mechanisms
Define and manage data quality rules, data lineage, and data classification to ensure transparency and accountability
Ensure organizational compliance with data governance policies, standards, and relevant regulatory requirements
Data Analysis and Reporting:
Conduct in-depth data analysis to uncover trends, patterns, anomalies, and areas for quality improvement
Define, implement, and maintain KPIs to monitor data quality, usability, and performance across domains
Deliver actionable insights using statistical techniques, SQL, Excel, Power BI, and AI-powered data quality tools to support data-driven decisions
Stakeholder Collaboration:
Engage with business users, data owners, and IT teams to understand data requirements and resolve quality issues effectively
Provide ongoing support and guidance on data quality best practices to ensure consistent understanding and adoption
Partner with Global Data Owners to define and agree on P1/P2/P3 KPIs for their respective data products
Monitor KPI status, proactively flag amber/red indicators, and initiate timely analysis and remediation efforts
Continuous Improvement:
Continuously enhance personal knowledge and skills in data quality management through training, certifications, and staying updated with industry advancements, contributing to ongoing improvement efforts