MetLife

Data Quality Management

• Collect and manage metadata, including Business Glossary and Data Lineage.
• Lead change management process by reviewing requests and routing to appropriate individuals
• Support identification and management of Critical Data Elements
• Coordinate the resolution of data governance issues: maintain issues list, follows-up with stakeholders on open 'Action Items'. Establishes ongoing communication with stakeholders to communicate work progress and outcome.
• Monitor data governance metrics and SLAs, assuring required KPI levels are within established thresholds

• Perform quality control process to ensure system configuration is in accordance with requirements
• Supports Consistency of Usage analysis; gathers all necessary data inputs for analysis, understanding analysis objectives/outcomes and developing the appropriate analysis method, preparing and delivering analysis results, offering remediation insights
• Supports the development of business rules and hypotheses to test the consistency of usage
• Supports Data Quality dashboard and “to-do list” requirements for monitoring and remediation
• Work with Data Stewards to coordinate the creation of data quality controls and monitoring tools.
• Implementation of Data Quality tool to deliver end to end Data Quality solutions
• Coordinate with Data Custodian, Data Domain Owners and Stewards for implementation of the Data Quality Business rules for corresponding dimensions
• Document and manage the Technical Data Quality rules

Knowledge, Skills and Abilities

• BA/BS in Business Administration, Communications, Accounting, Computer Science or Finance as well as any other related field of expertise

• 10+ years of experience in the Financial or Investment Services Industry in one or more of the following areas: Data Quality Development, Business Analysis, Data Management, Data Analysis & Reporting.

• Involved in each stage of data quality development cycle i.e. Analysis, Designing, Development, Testing and Documentation for data quality initiatives.
• Working knowledge of different data profiling methodologies, familiar with complex SQL queries and Data Quality rules on Data Quality Platform
• Working knowledge of Integration with different tools and technologies like Collibra, Power BI, etc.
• Working knowledge of Data Quality assets management, DQ Scorecards, Issue management and Data Quality rules implementation
• Proficient in Stakeholder management and project management.
• Working knowledge of reporting methodology for supporting Data Extraction, Data Quality with wide Reporting solution using Data Quality and reporting tools
• Rollout an enterprise-wide data quality framework, with focus on improvement of Data Quality framework
• Good exposure to UNIX or any scripting language
• Good exposure to DQ projects deployment
• Good exposure to Unit Testing and Production Support