Data Governance Analyst | Contract | Bank

Key Responsibilities

• Support periodic and ad-hoc data quality profiling, analysis, and dashboard reporting to monitor data quality metrics and identify data issues.
• Review, validate, and approve business metadata to ensure compliance with enterprise data governance standards and data definitions.
• Assist in thematic reviews and governance initiatives related to Data & Artificial Intelligence (AI) Risk Management.
• Perform data analysis to identify data inconsistencies, assess data completeness, validate intended data usage, and recommend remediation where necessary.
• Support the implementation and maintenance of data governance policies, standards, and quality controls across Consumer Banking & Wealth Management.
• Collaborate with business users, data owners, technology teams, and governance stakeholders to resolve data quality issues and improve data integrity.
• Prepare reports, dashboards, and documentation to support data governance activities and management reporting.
• Support investigations into data-related issues and contribute to continuous improvements in data quality and governance processes.
• Participate in ad-hoc projects and perform other duties assigned by the supervisor.

Requirements

• Diploma or Degree in Business Analytics, Information Technology, Computer Science, Computing, Business Studies, or a related discipline.
• 1–3 years of experience in Banking, Financial Services, Management Consulting, or a data-related role such as Data Management, Data Governance, Data Quality, Data Analysis, or Data Engineering.
• Good understanding of banking products, financial services processes, and associated data models.
• Solid proficiency in SQL for data extraction, analysis, and validation.
• Experience performing data profiling, data quality assessments, and data analysis.
• Excellent analytical and problem-solving skills with excellent attention to detail.
• Good verbal and written communication skills, with the ability to work effectively with both business and technical stakeholders.
• Familiarity with data governance and data management frameworks such as DAMA-DMBOK or DCAM (Data Management Capability Assessment Model) is advantageous.
• Exposure to data platforms and technologies such as Hadoop, Cloudera Data Platform (CDP), Python, PySpark, Apache Superset, or Teradata.
• Knowledge of Data Governance, Data Quality, Metadata Management, Master Data Management (MDM), or Data & AI Risk Governance concepts.