Build trusted data. Shape the future with AI.
We're looking for a curious, analytical, and business-minded Senior Data Governance Analyst to help improve how Commercial Banking manages, governs, and leverages data. This is not a traditional governance role focused solely on policies and documentation. You'll investigate complex data issues, identify root causes, build data quality controls, automate governance processes, and help modernize the function through AI and emerging technologies. Working closely with business leaders, technology teams, data stewards, and analytics partners, you'll ensure critical business data is accurate, trusted, and ready to support better decision-making. If you enjoy solving data problems, improving processes, working with SQL and automation tools, and finding innovative ways to turn trusted data into business value, we'd love to hear from you.
What You'll Do
- Design, develop, and maintain data quality controls across critical Commercial Banking data assets.
- Use SQL and Python to perform data profiling, reconciliation, monitoring, and root-cause analysis.
- Build automated frameworks to identify, monitor, and remediate data quality issues.
- Apply AI and agentic technologies to automate governance activities and improve operational efficiency.
- Partner with business, data, and technology teams to establish accountability for data quality and governance.
- Develop and maintain metadata, business definitions, lineage, and governance documentation.
- Support identification and remediation of critical data issues.
- Build dashboards and metrics that measure governance effectiveness and data quality performance.
- Contribute to regulatory, risk management, and compliance initiatives.
- Identify opportunities to modernize governance processes using emerging technologies.
- Promote a culture where data is treated as a strategic business asset.
What You'll Bring
Required Qualifications
- 5+ years of experience in Data Governance, Data Management, Data Quality, Data Analytics, or a related discipline.
- Strong SQL skills with experience analyzing and validating large datasets.
- Strong Python programming and automation experience.
- Experience designing and implementing data quality controls and monitoring frameworks.
- Knowledge of data governance principles