Data Governance Manager

Overview

We seek a seasoned Data Governance Manager to lead enterprise-wide efforts in managing data quality across a financial institution. This role is responsible for developing and executing strategies, standards, controls, and monitoring frameworks that align with organizational data governance and regulatory mandates.

Key Responsibilities

• Establish and enforce organization-wide data quality strategies, policies, procedures, and framework consistent with the bank’s Data Governance approach.
• Identify Critical Data Elements (CDEs) and design corresponding data quality rules, thresholds, controls, and key performance indicators (KPIs).
• Drive data quality improvement initiatives involving multiple banking sectors such as Retail, Corporate, Risk, Treasury, Finance, and Compliance.
• Develop and implement comprehensive data quality measurement frameworks encompassing dimensions like accuracy, completeness, consistency, validity, timeliness, and uniqueness.
• Create and maintain dashboards, reports, scorecards, and KPIs to track data quality trends and performance metrics.
• Lead investigative efforts to identify and resolve data quality issues using root cause analysis and corrective action planning.
• Collaborate with technology and data engineering teams to realize automated data quality controls and validation processes.
• Serve as subject matter expert in data quality, advising relevant business units, technology teams, and compliance divisions.
• Integrate data quality criteria into business processes, data models, applications, data pipelines, and reporting tools.
• Coordinate with data governance teams to uphold standards for data ownership, stewardship, lineage, and governance.
• Ensure regulatory and management reporting adheres to required data quality and control standards.
• Assess and deploy cutting-edge Data Quality, Governance, Catalog, and Analytics technologies.
• Utilize AI/ML techniques for enhanced data profiling, anomaly detection, and automation to elevate data quality monitoring.
• Lead modernization efforts involving migration from legacy data quality platforms to contemporary solutions.
• Provide advanced support in complex SQL query development, data profiling, analysis, and quality assessments.
• Manage data quality projects from initial requirements through design, testing, user acceptance, and deployment.
• Contribute to strategic planning by formulating recommendations aligned with business and technical roadmaps for Data Quality Management.

Required Qualifications and Experience

• At least 14 years of professional experience within Banking, Data Management, Governance, or related fields.
• Minimum 10 years directly involved in Data Quality and Governance roles, ideally in the Financial Services sector.
• Comprehensive understanding of banking workflows, systems, data territories, and regulatory frameworks.
• Proficiency in data management and governance frameworks, particularly DAMA-DMBOK and BCBS 239 standards.
• Familiarity with GDPR and other pertinent data protection regulations.
• Hands-on experience with Data Quality technologies, including Informatica Data Engineering Quality (DEQ), Enterprise Data Catalog, AXON, or comparable platforms.
• Advanced SQL skills necessary for complex queries, profiling, validation, analysis, and query optimization.
• Practical knowledge of Python utilized for data analytics, automation, and quality control tasks.
• Experience in creating Data Quality dashboards and reports using tools such as Power BI and Qlik.
• Deep understanding of data quality principles including profiling, validation, monitoring, remediation, and root cause diagnosis.
• Ability to implement automated data quality frameworks and controls.
• Experience working with large-scale datasets, Data Lakes, Warehouses, and enterprise data infrastructures.
• A proven record of leading 2–3 major data quality or governance projects to successful production deployment.
• Expertise in data lineage, metadata, ownership, stewardship, and governance practices.
• Collaborative experience with cross-disciplinary teams across business, technology, risk, compliance, and data engineering.
• Strong analytical, communication, and presentation skills capable of articulating complex data issues to diverse audiences.
• Bachelor's degree in Computer Science, Information Systems, Finance, Engineering, or related disciplines; Master’s degree is an advantage.