• Help on escalation points (e.g. Business has conflicting opinions on prioritization of a data element); • Heavily support the domain deployment activities; reviewing their activities during deployment (e.g. data cataloging tool usage, quality of definition, prioritization, sensitivity, retention etc.); • Conduct monitoring activities for each data governance component (e.g. Quality, Security); working together with other stakeholders as necessary; • Prepare training documents for tool usage and process execution; • Review and take action for domain ownership change requests (e.g. New domain request); • Facilitate cross-domain meetings and ensure that Working Group meeting is a functioning meeting; • Keep the committees up-to-date in terms of their structure; • Review enterprise level dashboards continuously to find improvement areas; • Track projects that rise out of remediation plans; • Collaborate with Security team to monitor the quality of selected privacy categories and compliance to established processes; • Monitor the tracking data storage and its impact on performance continuously (e.g. review a data retention heatmap) and approve data retiring by business or IT; • Support Data Governance Lead on framework, standard and tool selection/preparation and maintenance and collaborate with other teams as necessary (e.g. Security, Compliance); • Collaborate closely with business teams and data architecture team in the creation of standards; • Monitor compliance to standards in all areas (e.g. Review dashboards, question below target domains in committees etc.) and report to Data Governance Lead;
Namizədə tələblər
• 2+ years of experience with data / IT, data governance standards and practices in Banking; • Strong leadership experience in an enterprise or cross-functional role; • Strong interpersonal and communication/persuasion skills; • Strong project management leadership; • Experience in performance management metrics • Proven ability to coordinate cross functional teams of business, IT and other key stakeholders; • Strong skills in data analysis and quality profiling; • Familiarity with data quality issues and processes;