Senior Lead Technology Risk Officer | Technology Risk Management

Wells Fargo•Charlotte, NC

1d•Hybrid

About The Position

Wells Fargo is seeking a Senior Lead Technology Risk Officer in Corporate Risk Technology Risk Management. The position provides independent oversight and credible challenge of enterprise data tools and products supporting data governance, metadata management, and data lineage. It partners with data management, technology, and business teams to assess the design, implementation, adoption, and control effectiveness of metadata repositories, lineage platforms, and data quality tools, identifying and assessing data management risks across the enterprise. The role leads oversight of complex, high-risk data governance, metadata, and lineage tooling implementations across multiple business lines; evaluates risks associated with business and data platform decisions; and assesses whether enterprise metadata and lineage capabilities support regulatory reporting, risk data aggregation, model and AI use cases, and root-cause analysis. It also works with other risk disciplines to assess data tooling lifecycle risks, develops monitoring and risk insights, communicates and escalates data risk, and leads enterprise initiatives to advance data risk management transformation. The position is based at the listed Charlotte, North Carolina location and follows a hybrid model requiring work from a Wells Fargo facility at least four days per week, with the flexibility to work remotely one day per week. Visa sponsorship and relocation assistance are not available.

Requirements

7+ years of Technology Risk, Data Risk, or Data Management experience, or equivalent demonstrated through work experience, training, military experience, education.
Willingness to comply with the hybrid work model, including working from a Wells Fargo facility at least four days per week and remotely one day per week.
Ability to work at an approved location listed in the job posting.

Nice To Haves

Experience influencing senior executives and decision-makers and building credibility across large, complex organizations.
Experience leading enterprise-wide initiatives involving data management, risk management, technology, analytics, or business transformation.
Deep knowledge of data management disciplines, including data governance, data quality, metadata management, data lineage, critical data elements, controls, data sourcing, data requirements, and risk management practices.
Hands-on experience with, or oversight of, enterprise data governance, metadata, and lineage tools.
Familiarity with regulatory expectations for data governance and risk data aggregation, including BCBS 239, and relevant industry frameworks.
Understanding of how metadata and lineage capabilities support data quality issue management, data control attestation, and data product governance.
Experience providing independent oversight or challenge, governance, compliance, audit, or regulatory support.
Strong understanding of emerging data management, analytics, AI, and risk intelligence capabilities and how they can strengthen risk oversight and business decision-making.
Knowledge of risks associated with AI, advanced analytics, data modernization, digital transformation, and emerging technologies.
Experience leveraging analytics, automation, dashboards, and monitoring capabilities, including metadata- and lineage-driven insights, to identify emerging data risks and deliver actionable risk insights.
Ability to build trusted relationships across business, technology, AI, data management, data product and platform teams, and risk organizations.

Responsibilities

Identify, assess, and escalate data risks associated with enterprise data tools and products, including gaps in metadata completeness, lineage coverage, critical data element traceability, and data quality controls.
Lead independent oversight of highly complex, high-risk data governance, metadata, and lineage tooling implementations across multiple business lines.
Evaluate enterprise risks associated with strategic business and data platform decisions, including data tooling investments and vendor selections.
Assess whether end-to-end data lineage and metadata capabilities support regulatory reporting, risk data aggregation, model and AI use cases, and root-cause analysis.
Assess risks throughout the data tooling lifecycle in coordination with other risk disciplines, including technology and third-party risk.
Use metadata, lineage, and data quality insights to develop key risk indicators, dashboards, and monitoring capabilities that identify emerging data risks.
Engage and communicate with professionals and leaders across the enterprise to evaluate data risks in the context of business objectives and strategic initiatives.
Lead enterprise initiatives and virtual teams to advance companywide data risk management transformation.
Collaborate with peers, colleagues, and managers to evaluate, communicate, and escalate data risk.
Follow applicable risk programs, policies, procedures, and compliance obligations; monitor, identify, escalate, and remediate issues and make sound risk decisions.