VP, Data Quality Governance & Issue Management

PowerToFly; Dallas (TX); On-site; USD 120,000 - 210,000; Full time

Job summary

Morgan Stanley is seeking a Data Quality Governance Vice President to lead end-to-end management of Data Quality Issues within the enterprise DQ Program. You will implement and continuously enhance the DQ Issue Management framework, drive root cause analysis, remediation tracking, and closure validation in partnership with DDOs, FDO, and NFR functions.

You will embed sustainable practices across the data quality lifecycle, including data lineage, control frameworks, and remediation action plans,

Qualifications

• Bachelor's degree required; Master's preferred.
• 8+ years of experience in Data Quality, Issue Management, Data Governance, or Risk Management.
• Strong knowledge of regulatory expectations and governance frameworks.
• Experience with issue management platforms (e.g., IAT/OpenPages) and DQ tools.
• Advanced analytical skills and leadership experience.

Responsibilities

• Own and enhance the enterprise DQ Issue Management Framework.
• Lead end-to-end DQ issue lifecycle management.
• Enforce consistent application of issue severity, taxonomy, and escalation standards.
• Define and monitor KPIs/KRIs and reporting for issue trends and remediation.
• Partner with DDOs and NFR to ensure ownership and timely escalation.
• Deliver targeted training to strengthen DQ issue management.

Skills

Data Quality

Issue Management

Data Governance

Risk Management

Leadership

Cross-functional teams

Communication

Training

Education

Bachelor's degree

Master's degree preferred

Tools

IAT/OpenPages

Collibra

Informatica

Talend

Job description

Morgan Stanley is seeking a Data Quality Governance Vice President to lead end-to-end management of Data Quality Issues within the enterprise DQ Program. You will implement and continuously enhance the DQ Issue Management framework, drive root cause analysis, remediation tracking, and closure validation in partnership with DDOs, FDO, and NFR functions.

You will embed sustainable practices across the data quality lifecycle, including data lineage, control frameworks, and remediation action plans,