EDUCATION:

Master’s degree in Computer Science, Information Systems/Technology, Business administration or Data Science

WORK EXPERIENCE:

Minimum 6-8 years of experience in Financial Services with deep knowledge in various Data Management disciplines: Data Analytics, Data Quality, Business Intelligence, Data Governance
Job ID JB1100012200

JOB PURPOSE:

To assist and support the Head of Data Governance in designing and implementing policies, standards, processes and systematic methods to measure and improve the reliability, integrity of DIB’s data and ensure that the data quality standards are achieved to support decision making of the bank and risk tolerance is based on trusted data.

KEY RESPONSIBILITIES:

Work with stakeholders across DIB to identify the business needs that would benefit from improved data and prioritize data quality initiatives that will yield a high business value
Lead the data quality initiatives and efforts to ensure and maintain compliance to regulatory obligations
Develop data quality policies, standards, frameworks and KPIs that will support a sustainable approach to achieving high data quality standards
Implement a data quality management platform that will integrate with business applications and/or data warehouses to monitor the quality of the data across the data lifecycle and identify obsolete data for archival and/or purging in line with data retention obligations
Execute automated data quality rules as defined by the metadata teams to assess the adherence to data quality definitions and ensure timely remediation of exceptions
Identify approved authoritative external/internal data sources that can be leveraged to enrich and improve the quality of DIB data
Execute ongoing data profiling and data audits to understand trends and user behaviors that need to be controlled and improved across all data entry points
In collaborations with data stewards, develop and implement data issue management workflows that will detect, log, track and report data issues to relevant stakeholders and ensure resolution of such issues are completed within set service level agreements
Establish a business-friendly data quality dashboard and reporting that will monitor data quality metrics such as (but not limited to) data completeness, conformance, validity, consistency, uniqueness and timeliness across all Master data domains (e.g Customer domain, Risk & Finance domain, Product domain) and aggregate these to establish an overall data quality score