Data Quality Manager at I&M Bank

Job Purpose:

• The Data Quality Manager will be responsible for establishing and maintaining robust data quality frameworks, policies, and practices across the bank.
• This role ensures that data quality principles are implemented across the Bank which will enable support strategic data driven decision-making, regulatory compliance, and operational efficiency.

Key Responsibilities:
Data Quality Strategy and Implementation: 

• Assist data governance office in developing, implementing, and maintaining comprehensive data quality strategies, policies, and procedures to ensure data integrity across the bank. This includes defining critical data elements, establishing data quality rules, and setting measurable quality targets.

Data Quality Monitoring and Reporting: 

• Design and deploy robust data quality monitoring mechanisms, including dashboards and reports, to track key data quality metrics (e.g., accuracy, completeness, consistency, timeliness, uniqueness, validity, relevance, integrity) and Key Performance Indicators (KPIs).
• Regularly assess data quality performance, identify trends, and report findings to Head of Data Governance.

Data Governance and Compliance: 

• Work with data governance office to establish and enforce data governance frameworks. Ensure compliance with internal data quality standards, external regulatory requirements (e.g., KDPA, FATCA, CRS etc..), and industry best practices.
• Participate in the development and enforcement of data ownership and stewardship models.

Data Quality Assessments and reviews: 

• Conduct regular data quality assessments and reviews to identify data defects, root causes, and potential risks. Develop and oversee remediation plans in collaboration with data owners and technical teams to resolve data quality issues promptly and effectively.

Data Cleansing and Enrichment Initiatives: 

• Lead and manage data cleansing, standardization, and enrichment projects to improve the overall quality and usability of data assets with Bank stakeholders (data owners and data stewards). This involves working with data engineers as well and other technical teams to implement automated data quality processes and tools.

Cross-Departmental Collaboration: 

• Collaborate effectively with various departments, including IT, business units, analytics, and legal, to foster a data quality-aware culture. Provide expert guidance and support on data quality best practices and solutions.

Training and Awareness: 

• Develop and deliver training programs and awareness campaigns to educate employees across the organization on data quality principles, policies, and their roles in maintaining high data quality standards.

Tool and Technology Management: 

• Evaluate, select, and implement data quality tools and software to automate data profiling, validation, cleansing, and monitoring processes. Stay abreast of emerging data quality technologies and methodologies.

Key Measures:

• Data Quality Framework, Policies, Procedures, Standards and Metrics: Assist DGO in developing and maintaining the bank’s data quality framework, policies, procedures, standards and metrics.
• Regulatory Compliance: Ensure compliance with regulatory and internal risk management data standards.
• Data Stewardship: Manage data stewardship programs to drive accountability especially with data quality principles.
• Data Quality Management: Develop and implement and monitor data quality controls, standards and metrics across the bank.
• Training & Awareness: Build a culture of data responsibility through continuous data quality trainings and stakeholder engagements.

Education Requirements:

• Bachelor’s or master’s in data science, Information Systems, Computer Science, or related field.

Professional Qualifications / Membership to professional bodies:

• Six Sigma or Lean Data Quality Certification.
• ISO 8000 Data Quality Certification.
• Any other Data Quality Certifications.

Work Experience:

• 5+ years in data management, data governance, or analytics, with at least 2 years in a data quality role. 
• Proven experience in banking or financial services is highly preferred.
• Familiarity with data governance tools, data catalogues, and data quality management platforms.
• Familiarity with industry frameworks (e.g., DAMA-DMBOK, ISO 8000, DCAM).

Competencies:

• Strong analytical and problem-solving skills.
• Proficiency in SQL, Python and BI platforms.
• Excellent communication and stakeholder management.
• Deep understanding of data quality and metadata management.
• Ability to lead cross-functional initiatives.
• Knowledge of data privacy and compliance regulations.