Data Governance Manager

About the job
We are looking for an experienced Data Governance Lead to drive enterprise-wide data quality management across the bank. The role will be responsible for defining and implementing data quality strategies, standards, controls, monitoring frameworks, and remediation processes aligned with the bank’s data governance framework and regulatory requirements.

Responsibilities

Define and implement enterprise data quality strategies, policies, standards, procedures, and frameworks aligned with the bank’s Data Governance strategy.
Identify and define Critical Data Elements (CDEs) and establish appropriate data quality rules, thresholds, controls, and KPIs.
Drive data quality improvement initiatives across Retail, Corporate, International, Treasury, Risk, Finance, Compliance, and other support functions.
Design and implement data quality measurement frameworks covering accuracy, completeness, consistency, validity, timeliness, and uniqueness.
Develop and maintain Data Quality dashboards, reports, scorecards, and KPIs to monitor data quality trends and performance.
Identify, investigate, and remediate data quality issues through root cause analysis, impact assessment, and corrective action plans.
Work with technology and data engineering teams to implement automated data quality controls, validation rules, monitoring, and remediation processes.
Act as a Data Quality SME and provide guidance to business, technology, risk, finance, compliance, data owners, and data stewards.
Embed data quality requirements into business processes, data models, applications, data pipelines, and reporting solutions.
Collaborate with data governance teams to ensure effective implementation of data ownership, stewardship, lineage, and governance standards.
Support regulatory and management reporting by ensuring critical datasets meet defined quality and control requirements.
Evaluate and implement modern Data Quality, Data Governance, Data Catalog, and Analytics technologies.
Leverage AI/ML-based data profiling, anomaly detection, and automation to improve data quality monitoring and issue identification.
Lead data quality platform modernization initiatives, including migration from legacy solutions to modern tools.
Provide technical guidance on complex SQL queries, data analysis, profiling, and data quality assessments.
Lead data quality initiatives from requirements gathering through design, implementation, testing, UAT, and production go-live.
Prepare strategic recommendations and contribute to the Data Quality Management roadmap aligned with business and technology objectives.

Requirements

14+ years of overall experience in Banking, Data Management, Data Governance, Data Quality, or related areas.
Minimum 10 years of hands-on experience in Data Quality and Data Governance, preferably within the Banking/Financial Services industry.
Strong understanding of banking processes, systems, data domains, and regulatory requirements.
Strong knowledge of Data Management and Data Governance frameworks, preferably DAMA-DMBOK and BCBS 239.
Knowledge of GDPR and other applicable data protection, governance, and regulatory requirements.
Strong hands-on experience with Data Quality tools and technologies, preferably:
Informatica Data Engineering Quality (DEQ)
Informatica Enterprise Data Catalog
Informatica AXON
Other enterprise Data Quality/Governance platforms
Strong experience with SQL, including writing complex queries, data profiling, validation, analysis, and query optimization.
Working knowledge of Python for data analysis, automation, and data quality processes.
Experience developing Data Quality dashboards, scorecards, and reporting solutions using tools such as Power BI and Qlik.
Strong understanding of Data Quality dimensions, profiling, validation, monitoring, issue management, remediation, and root cause analysis.
Experience implementing automated data quality controls and monitoring frameworks.
Experience working with large-scale datasets, Data Lakes, Data Warehouses, and enterprise data platforms.
Experience modernizing or migrating legacy Data Quality platforms and processes to modern technology solutions.
Proven experience successfully delivering 2–3 large-scale data quality/data governance engagements through production go-live.
Strong understanding of data lineage, metadata, data ownership, data stewardship, and data governance concepts.
Experience working with cross-functional stakeholders including business, technology, risk, finance, compliance, and data engineering teams.
Excellent analytical and problem-solving skills with the ability to investigate complex data issues and develop practical solutions.
Strong communication and presentation skills, with the ability to explain complex data concepts to both technical and non-technical stakeholders.
Bachelor's degree in Computer Science, Information Systems, Finance, Engineering, or a related field. Master's degree is preferred.