Data Quality Governance, VP

Morgan StanleyAddison, TX
4d$108,000 - $184,500

About The Position

We're seeking someone to join our team as a Data Quality Governance VP in the Data Governance & AI Non-Financial Risk team to provide team leadership and also champion policy compliance, improve data quality across enterprise data assets, and develop training programs to enhance data literacy and reinforce governance standards. In the Legal & Compliance division, we assist the Firm in achieving its business objectives by facilitating and overseeing the Firm's management of legal, regulatory and franchise risk. This is a Vice President level position within the Data Quality team which is responsible for implementing, assessing, and enhancing data quality frameworks across the organization, including BCBS 239, risk data aggregation, data lineage, and DQ control frameworks. Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

Requirements

  • Bachelor's degree and/or Master's preferred.
  • Minimum of 8 years of experience in data quality, governance, architecture, or modeling.
  • Deep understanding of data lifecycle management and DQ tools.
  • Advanced proficiency with Excel or other analytics tools.
  • Strong analytical and communication skills.
  • Proven experience in training and mentoring others.
  • Demonstrated leadership and project management capabilities.
  • Experience with metadata platforms and DQ tools (e.g., Collibra, Informatica, Talend).
  • Strong understanding of regulatory and governance frameworks.
  • Ability to lead cross-functional teams and manage complex initiatives.
  • Typically, 8+ years' relevant experience would generally be expected to find the skills required for this role

Responsibilities

  • Represent and advocate for the Data Governance Office as a Data Quality SME.
  • Lead Data Quality implementation efforts, including working groups and framework adoption.
  • Maintain and enhance data governance taxonomies, inventories, and metadata tagging.
  • Oversee and manage DQ issues, remediation, and control effectiveness assessments.
  • Apply the DQ Program framework to risks, metrics, and monitoring practices.
  • Build strong relationships with business units, data stewards, compliance, and risk teams.
  • Provide expert guidance to advance data-centric processes.
  • Maintain and enhance data and information policy documents.
  • Train team members and DQ officers on governance standards and metrics.
  • Develop and deliver training programs that promote data literacy.
  • Support audits and regulatory reviews related to data quality.
  • Drive continuous improvement through root-cause analysis and remediation.
  • Maintain documentation and training materials related to data governance.
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