Enterprise Data Strategy - Permissible Data Use leader

Wells Fargo Bank•Charlotte, NC

1d•Hybrid

About The Position

Wells Fargo is back in the office collaborating for fabulous outcomes! This is a hybrid position in the office three days a week. There is no visa sponsorship or visa transfers for this role. About this role: We are seeking a Senior Lead Data Management Analyst within the Chief Data Office (CDO) reporting to the head of Enterprise Data Strategy and Execution. The position plays a central role in establishing and operating centralized enterprise governance for permissible data use, ensuring that data are used only for approved purposes and in compliance with legal, regulatory, and internal policy requirements. As the firm continues to expand its data, analytics, and AI capabilities, the CDO is evolving its data use governance model to be more consistent, transparent, and scalable across data domains and lines of business. This role will contribute to updated policy and roles, define processes, and controls; drive tooling and reporting enhancements; and ensure strong integration with related governance frameworks, including AI governance, Model Risk Management, privacy, and third‑party risk management. The work performed in this role is critical to mitigating legal, compliance, reputational, and financial risk while enabling responsible data use and innovation.

Requirements

7+ years of Data Management, Business Analysis, Analytics, or Project Management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Nice To Haves

7+ years of experience in enterprise data governance, data risk management, privacy‑adjacent controls, or related disciplines within a large, complex organization.
Demonstrated practitioner experience designing and operating permissible data use governance, including purpose limitation, approvals, exceptions, monitoring, and evidence management.
Experience governing enterprise-wide data use, with strong understanding of legal, regulatory, contractual, and internal policy requirements.
Hands‑on experience engaging with AI governance and/or Model Risk Management processes, particularly as they relate to data sourcing and data permissions.
Strong background in process design, control development, and documentation, including sustainable operating models and audit‑ready artifacts.
Experience defining governance requirements and partnering with tooling or platform teams to deliver scalable workflow and reporting capabilities.
Proven ability to influence cross‑functional stakeholders (legal, compliance, privacy, information security, analytics, technology, third‑party risk) without direct authority.
Excellent written and verbal communication skills, including the ability to develop clear, well‑structured executive level presentations and governance materials.
Strong analytical and critical‑thinking skills, with the ability to identify risk patterns and recommend targeted control enhancements.

Responsibilities

Establish and operate centralized enterprise governance for permissible data use, covering all data types across Data Domains and lines of business.
Contribute to enterprise policies, procedures and roles for permissible data use in partnership with Enterprise Data Governance and key risk and control stakeholders.
Design, document, and maintain end‑to‑end processes and controls for data use governance, including intake, review, approval, exception handling, evidence management, monitoring, and auditability.
Ensure effective and efficient engagement with AI governance processes, embedding data use requirements into analytics, AI, and model development and lifecycle activities.
Align data use governance with related enterprise policies and frameworks as appropriate, including legal, compliance, privacy, information security, Model Risk Management, and third‑party risk management.
Define requirements and drive prioritization of tooling enhancements with product‑owning organizations to support scalable workflows, approvals, documentation, and reporting.
Develop operational reporting and metrics to provide transparency into data use activity, adherence to standards, exceptions, and emerging risk themes.
Provide guidance and enablement to data domains and lines of business, including playbooks, templates, standards, and training materials to support consistent execution.
Leverage industry benchmarks and best practices to continuously improve the firm’s approach to governing permissible data use and responsible AI.
Identify, escalate, and drive remediation of data use governance risks, including root‑cause analysis and enhancements to preventative and detective controls.
Communicate clearly and effectively with senior stakeholders.