Technical Responsibilities:
- Data Quality Assessment: Conduct regular data quality assessments to identify and address data anomalies, inconsistencies, and inaccuracies.
- Data Profiling: Utilize data profiling techniques to analyze data attributes, identify data quality issues, and assess data completeness.
- Data Cleansing: Develop and implement data cleansing processes to correct errors, standardize data formats, and improve data quality.
- Data Validation: Create and implement data validation rules to ensure data integrity and consistency.
- Metadata Management: Manage metadata repositories and ensure accurate and up-to-date metadata is maintained.
- Tool Utilization: Proficiently use data governance and data quality tools like IDMC or Collibra to manage data lineage, impact analysis, and data quality metrics.
- Data Governance Framework: Contribute to the development and maintenance of a comprehensive data governance framework, including policies, standards, and procedures.
Functional Responsibilities:
- Stakeholder Engagement: Collaborate with business users, data owners, and IT teams to understand data requirements and ensure data quality meets business needs.
- Data Stewardship: Support data stewards in their role of ensuring data quality and compliance.
- Data Quality Metrics: Develop and track key data quality metrics to measure the effectiveness of data governance initiatives.
- Issue Resolution: Investigate and resolve data quality issues in a timely manner.
- Continuous Improvement: Identify opportunities for process improvement and implement best practices to enhance data quality.
- Change Management: Manage changes to data definitions, data sources, and data processes to minimize disruptions.
