Manager – Data Quality and Operations

Manager – Data Quality and Operations

Requirements

• Bachelor’s degree or higher in a quantitative field such as Finance, Mathematics, Statistics, Business Analytics, or a related discipline.
• 2+ years of experience in data analysis, preferably in risk management industry.
• Demonstrated advanced experience in SQL is required for data extraction, manipulation, and analysis.
• Proven experience with data visualization tools, particularly Tableau.
• Advanced knowledge in Excel particularly in Pivot Tables, VBA, Macros are required for this role.
• Knowledge of data governance and data management principles.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills.
• Ability to work independently and as part of a team.
• Strong attention to detail.

Responsibilities

• Develop and implement data quality rules, checks, and validation procedures for data used in capital measurement calculations (e.g. RWA, capital ratios).
• Identify, investigate, and resolve data quality issues, working closely with data owners and IT teams.
• Collaborate with IT and business teams to implement data quality improvements.
• Conduct regular data quality assessments to identify and resolve data discrepancies, inconsistencies, and errors and initiate corrective actions.
• Monitor data pipelines and data flows to ensure data integrity and completeness.
• Monitor data quality metrics and generate regular reports on data quality performance.
• Implement data cleansing and data enrichment processes in production.
• Contribute to the development and implementation of data governance policies, standards, and procedures for capital data.
• Support the definition and maintenance of data dictionaries, data lineage, and metadata.
• Participate in data governance meetings and initiatives.
• Ensure compliance with regulatory requirements related to data governance and data quality.
• Utilize SQL and other techniques (Python, Spark, Shell Script) to extract, manipulate, and analyze large datasets from various sources including automation of repetitive tasks.
• Perform root cause analysis to identify the source of data quality issues and propose solutions.
• Investigate data anomalies and discrepancies to ensure compliance with regulatory requirements.
• Very high focus on documentation is required in this role as the process in heavily audited.
• Develop and maintain comprehensive documentation of data quality processes, rules, and procedures.
• Support regulatory audits and examinations by providing data quality documentation and analysis.
• Stay up to date with changes in regulatory requirements and industry best practices.
• Ensure data quality meets regulatory requirements as identified by senior management.
• Create interactive dashboards and visualizations using Tableau/other visualization tools to communicate data quality metrics and trends.
• Develop ad-hoc reports and analyses to support business and regulatory needs.
• Present data findings to senior management.

Preferred Qualifications

• Automation skills using Python or other scripting languages.
• Knowledge of distributed computing and cloud data warehousing (e.g. Spark, DataBricks, Snowflake)
• Knowledge of bank capital measurement concepts (e.g., RWA, capital ratios) is highly desirable.
• Knowledge of risk management principles and practices.
• Experience with data quality tools and platforms.
• Familiarity with data warehousing and ETL processes.
• Certifications related to data management or financial risk management.