Job Summary:

• Defining data quality rules ensuring data is measured and trusted. 
• Working with project teams to define data quality requirements as well as ensuring ongoing assessments of data quality.
• Development of definitions, data quality rules, thresholds, and standard metrics of quality for data elements that support critical business processes.
• Development of controls to mitigate data quality risks including data quality plan development, implementing data quality rule checks, monitoring data quality results, reports and dashboards
• Performing data profiling on large datasets to determine data quality and integrity.
• Documentation and reporting data quality metrics and issue remediation.
• Identify and manage existing and emerging data quality risks that stem from business activities.
• Support compliance assessment process by reviewing and documenting failures from data quality compliance assessment checks.
• Support delivery of information in accordance with Information Governance standards and data management practices through documentation, collaboration, and execution of defined processes.
• Review, validate, and record metadata and data quality information.
• Defining and documenting metadata to ensure the information is captured and available for consumers. 

Skills on Resume:

• Data Quality Rules (Hard Skills)
• Quality Requirements (Hard Skills)
• Data Profiling (Hard Skills)
• Risk Mitigation (Hard Skills)
• Metrics Development (Hard Skills)
• Compliance Assessment (Hard Skills)
• Metadata Management (Hard Skills)
• Reporting Standards (Hard Skills)

Job Summary:

• Work with stakeholders across levels to identify data quality requirements
• Define the data quality metrics, improve data quality strategy and challenge and improve the overall data design and metrics
• Perform ad hoc data quality assessments for new data sources and potential data quality issues
• Automate data quality monitoring by developing data pipelines and visualizations
• Improve the documentation on available data sources, promote data-driven culture, and spread knowledge of data sources and data tools.
• Capturing the data flow through Data Lineage. 
• Working with project teams or support teams to define, redefine, or continue maintenance of the metadata.
• Maintain metadata repository and proper metadata association.
• Follow written risk and compliance policies and procedures for business activities.
• Identify opportunities for improvement in processes. 
• Participate in development of best practices and tools based on business needs.
• Participate and possibly lead discussions with cross-functional teams to resolve data quality issues.

Skills on Resume:

• Data Quality Requirements (Hard Skills)
• Quality Metrics Definition (Hard Skills)
• Data Assessment (Hard Skills)
• Automation Development (Hard Skills)
• Documentation Improvement (Hard Skills)
• Data Lineage (Hard Skills)
• Metadata Maintenance (Hard Skills)
• Process Improvement (Hard Skills)

Job Summary:

• Perform reference data analysis on long-term and ad-hoc projects including data augmentation and normalization.
• Participate in internal and external decision-making processes utilizing expertise in reference data and insights.
• Support tool creation and refinement through functionality documentation, testing, and UAT collaboration with the product, engineering, and reference data management teams.
• Create and maintain policies, procedures, and technical documentation.
• Collaborate with subject matter experts and delivery teams QA to ensure accurate test plans. 
• Author and execute testing requirements, scripts, defect reporting, and test cases.
• Facilitate various reference data meetings and discussions to process and finalize data strategy for data accuracy and consistency through sound judgement including the appropriate audience.
• Communicate with internal and external partners to inform, update, or consult on critical data decisions.
• Create, update, and review defect tracking logs and work with project teams to ensure all defects are resolved across projects.
• Collect, analyze, interpret, reconcile, and validate data from multiple sources and formats to discern information relevancy and consistency.
• Identify, research, and resolve conflicting and inconsistent information.

Skills on Resume:

• Data Analysis (Hard Skills)
• Strategy Development (Hard Skills)
• Documentation Management (Hard Skills)
• QA Collaboration (Hard Skills)
• Testing Requirements (Hard Skills)
• Defect Tracking (Hard Skills)
• Data Validation (Hard Skills)
• Stakeholder Communication (Hard Skills)