VP: Data Governance & Modeling for AI-Driven Finance

Archer; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

BNY seeks a Vice President for Data Governance & Data Modeling in NYC to advance enterprise data management. You will design, implement, and govern data models across conceptual, logical, and physical layers while partnering with business and technology teams to ensure data standards and controls.

Ideal candidates bring hands-on data modeling, PL/SQL, and strong governance experience in financial services, with a track record of leading teams and driving data-driven decision making.

Qualifications

• Bachelor’s degree or equivalent in CS or related field.
• 5+ years in finance industry data roles.
• Hands-on data modeling and PL/SQL.
• Strong data governance knowledge (quality, lineage, metadata, controls).

Responsibilities

• Design and maintain data models (conceptual, logical, physical).
• Lead data governance activities including quality and lineage.
• Define data standards and controls with business teams.
• Remediate data issues to improve consistency and usability.
• Develop scalable data solutions for reporting and analytics.
• Mentor data professionals and promote a data-driven culture.

Skills

Data modeling

Data governance

PL/SQL

Data architecture

Leadership

Communication

AI familiarity

Cloud data platforms

Finance domain experience

Regulated environment

Education

Bachelor’s degree

Advanced degree in Computer Science

Tools

Metadata management tools

Data visualization tools

Cloud data platforms

Job description

BNY seeks a Vice President for Data Governance & Data Modeling in NYC to advance enterprise data management. You will design, implement, and govern data models across conceptual, logical, and physical layers while partnering with business and technology teams to ensure data standards and controls.

Ideal candidates bring hands-on data modeling, PL/SQL, and strong governance experience in financial services, with a track record of leading teams and driving data-driven decision making.