Position: Lead- Data Quality Emiratized role
Sub Division:
Data Analytics and Artificial Intelligence Company Description Now it’s your time to join the #1 bank in the Middle East and one of the most prestigious financial companies in the region. Shaking up the world of banking requires a lot of smarts and skill. We’re looking for the brightest and best to help us reach our goals and we’ll also help you reach yours.
Your success is our success as you grow stronger in your career. Join us and leave a legacy of your own, as a pioneer in both the company and the industry.
Job Description The job holder is responsible for leading the design, development and implementation of the Data Governance program, specifically those relating to data quality, as part of the Data Governance Office. They are accountable for maintaining direction and ensuring alignment with business objectives regarding how data is managed across the organisation.
The job holder is also a key member of the broader data management group across the organization and is expected to play an important role in influencing and providing direction to the wider data management community.
Strategic responsibilities
Lead the development of the organizational Data Strategy as well as lead data management in line with strategic business objectives and FAB cultures and values.
Manage and support the AVP data governance and data quality in the development and oversight of data governance framework, standards, practices, policies and processes.
Lead the development of the Data Governance Office as a center of excellence committed to ingraining a data-driven decision-making culture across the organization, teaming with external partners, and offering end-to-end data services across business and support groups.
Lead and provide direction in the monitoring and analysis of the latest strategic, technological, and regulatory trends within the organisation and on a global scale.
Promote good data quality practices and the management of data as a strategic asset.
Core responsibilities
Lead the production of information on performance and quality standards for data within the organization.
Gather and create inputs for the management and reporting of data SLA and KPI’s, including monitoring of data quality dashboards, SLA breaches, etc., ensuring adherence to agreed SLA targets and demonstrating improvement against agreed targets.
Lead and provide guidance and all the necessary support to the AVP data governance and data quality in managing and resolving data quality issues, providing advice and guidance to all business areas.
Advise on targets and monitoring standards with stakeholders for data entry and data collection undertaken.
Responsible for leading/directing the development of DQ measurement/reporting/control capabilities.
Responsible for leading/directing the development and maintenance of data quality rules.
Responsible for leading/directing the development and maintenance of DQ profiling tools/methodologies.
Responsible for leading the development and ongoing maintenance of data definitions, standards, lineage and other data quality artifacts as part of the data catalogue.
Lead the development, maintenance and management of organizational reference data.
Provide subject matter expertise on systems/process developments to control and improve data quality.
Lead the development of Data Quality Monitoring tools and DQ Dashboards and provide direction to subordinates.
Support and guide the RCA team with analyzing data across applications from a Data Quality standpoint.
Guide and provide necessary support to different Business units from a DQ point of view.
Communication Internal:
The role requires establishing strong working relationships with all business groups and support functions of the organization at various levels to ensure continued buy-in for the Data Governance Model.
External:
The role requires regular interactions with vendors, data partners, consulting partners, and regulatory and governmental bodies.
KPIsDelivery against planned DQ roadmap activities.
Outstanding ‘high criticality’ data issues.
Increase in stakeholder opinion of DQ.% Improvement in DQ for key data elements.
Feedback from peers,…
