Technology Director - Credit Risk

Wells Fargo Bank•Charlotte, NC

About The Position

Wells Fargo’s Enterprise Functions Technology group provides technology solutions and support to Risk and other enterprise business lines. Within this group, the Credit Risk Technology Team is seeking a Technology Director to lead a significant portfolio of critical data platforms, business applications, modernization initiatives, and production operations for Corporate Risk stakeholders. The role balances reliable operation of legacy platforms with the multi-year Credit Risk 360 transformation. This includes developing modern data models and AI-ready semantic capabilities, modernizing applications and portals, delivering technology-mandated changes and platform migrations, and decommissioning outdated technology. The Director leads a large global organization of engineering managers, technical leaders, and engineers; manages investment and capacity; and partners with product, Risk, Finance, data, architecture, controls, and operations leaders. The position oversees enterprise Credit Risk repositories, analytical data services, reporting capabilities, and business applications. It is accountable for delivering governed, reconciled, traceable, and auditable data; maintaining business continuity and regulatory readiness; protecting production stability; and improving engineering delivery and operational resilience. The role also advances modern, scalable data and application architecture, DevSecOps, automation, and responsible AI adoption, while managing budgets, vendors, workforce plans, and stakeholder relationships. The position may require travel up to 20%. The stated base pay range is $215,000 to $355,000. Employees may also be eligible for incentive opportunities.

Requirements

At least 10 years of Technology Strategic Leadership experience, or equivalent demonstrated through work experience, training, military experience, or education.
At least 5 years of experience leading Credit Risk, Finance Risk, regulatory data, risk analytics, or comparable enterprise risk technology portfolios.
At least 5 years of experience managing critical data repositories and business applications across build, run, modernization, migration, and decommissioning lifecycles.
At least 5 years of experience with modern data platforms, distributed systems, APIs, cloud-ready architectures, security, resiliency, and operational risk.
At least 5 years of experience partnering effectively with product, Risk, Finance, data, architecture, controls, audit, and operations stakeholders.
At least 4 years of management or leadership experience.
At least 4 years of experience leading engineering managers, technical leaders, and enterprise-scale software and data delivery teams.
At least 4 years of experience leading complex transformation programs in a regulated enterprise, including investment planning, capacity management, and executive governance.

Nice To Haves

Deep knowledge of Credit Risk data, allowance and forecasting, risk reporting, or related risk-management processes and controls.
Experience modernizing large data and application estates while maintaining regulatory compliance, delivery continuity, and operational stability.
Experience with cloud-ready data architecture, lakehouse or distributed data platforms, Spark/PySpark, Dremio or comparable semantic layers, APIs, microservices, and modern web applications.
Experience with legacy and enterprise integration technologies, including Ab Initio, SSIS, mainframe platforms, and large-scale batch processing.
Demonstrated ability to convert strategy into executable roadmaps, investment choices, measurable outcomes, and sustained delivery.
Experience applying AI and automation to engineering delivery, data interaction, or business workflows with appropriate governance and controls.
Strong executive communication, influence, financial management, vendor management, and organizational leadership skills.
Experience supporting regulatory examinations, audit engagements, technology risk remediation, and control programs.

Responsibilities

Lead a global organization of engineering managers, technical leads, and engineers responsible for Credit Risk platforms, applications, delivery, and production operations.
Own technology strategy, roadmaps, delivery outcomes, operational health, and investment planning for the assigned Credit Risk portfolio.
Maintain business continuity and regulatory readiness across critical legacy platforms while accelerating modernization and decommissioning.
Deliver the Credit Risk 360 target state, including platform capabilities, core data models, curated business use cases, modernized workflows, and migration from legacy platforms and portals.
Direct delivery for Financial Risk Data, ACL and loss forecasting, and related Credit Risk data and application capabilities as assigned.
Drive technology-mandated changes, Data Private Cloud and target-state data-platform migrations, application upgrades, vulnerability remediation, resiliency improvements, and retirement of end-of-life technology.
Advance AI-enabled engineering and business capabilities, including AI-ready data, semantic layers, automated regression and refactoring, and controlled agentic solutions.
Partner with product, Corporate Risk, Finance, architecture, data, operations, controls, audit, and enterprise technology teams to set priorities and resolve dependencies.
Manage budgets, workforce plans, vendors, sourcing, and engineering capacity across run-the-business and change-the-business commitments.
Establish measures for delivery predictability, data quality, platform health, operational resilience, engineering productivity, risk reduction, and business value.
Build a culture of ownership, transparency, technical excellence, succession, and continuous improvement.
Oversee the design, build, maintenance, and enhancement of enterprise Credit Risk repositories, analytical data services, reporting capabilities, and business applications.
Deliver trustworthy, governed, and reconciled data from a large and complex upstream ecosystem, with strong lineage, controls, observability, and auditability.
Improve delivery through disciplined prioritization, dependency management, release governance, capacity planning, and measurable operational readiness.
Protect production stability through incident prevention, recovery readiness, performance and capacity management, vulnerability remediation, and elimination of key-person dependencies.
Ensure production change commitments meet quality, traceability, control, and supportability expectations.
Establish the data layer as the authoritative source for Credit Risk calculations, controls, and reusable business logic.
Advance modern target-state patterns using scalable data processing, curated data products, governed semantic access, APIs, and user-centric web experiences.
Promote API-first, modular, resilient, and cloud-ready architecture while reducing unnecessary duplication across compute, storage, and presentation layers.
Drive DevSecOps, automated testing, continuous delivery, platform engineering, site reliability, and objective engineering-quality measures.
Apply AI responsibly for engineering productivity and business enablement, with clear controls, human oversight, and measurable adoption and value.
Provide leadership across Java, .NET, Python, JavaScript, Big Data, Spark/PySpark, Ab Initio, SSIS, APIs, and mainframe technologies in a mixed modern and legacy environment.
Lead, mentor, and develop a high-performing global engineering organization with clear ownership for platforms, applications, delivery, and operations.
Build trusted stakeholder partnerships and communicate strategy, priorities, trade-offs, delivery progress, risks, and decisions clearly and transparently.
Develop engineering managers and technical leaders who can independently drive complex, cross-platform outcomes.
Manage strategic investments, vendor relationships, sourcing models, and workforce plans with financial discipline.
Create an inclusive culture that encourages constructive challenge, enterprise thinking, innovation, accountability, and continuous learning.