About this role: Wells Fargo is seeking a Lead Risk Analytics Consultant/GCP Engineer to support the Model Risk Management (MRM) organization as part of the Model Computing and Governance Platform team . This role is highly technical and requires strong hands‑on experience with cloud engineering, platform migration, and production‑level python coding to support model validation, governance, and analytics platforms. The successful candidate will join a high‑visibility team responsible for building, maintaining, and enhancing the technology platforms enabling Model Risk Management (MRM) and Model Development Centers of Excellence. This role requires the ability to work directly on Google Cloud Platform (GCP) and OpenShift , write or re‑write python code , and support platform migrations while ensuring system reliability, data integrity, and operational excellence. Professional presence, strong communication, and excellent documentation skills are essential for collaborating across MRM, model governance, audit, infrastructure, and engineering partners. In this role, you will: Cloud Engineering & Platform Work Demonstrate working proficiency on distributed systems and cloud platforms (GCP) and data storage solutions. Participate in cloud migration initiatives , including modernizing existing code, performance optimization, and addressing compatibility issues. Collaborate with GCP and OpenShift infrastructure teams to diagnose and resolve platform‑level incidents or resource issues. Operational & Production Responsibilities Oversee production processes, including data reconciliation, pipeline reliability , and creation of clear, comprehensive documentation. Maintain and enhance observability tooling to ensure platform stability and fast issue detection. Development & Automation Build and maintain automation using Python, R, SQL, Pandas, PySpark , or similar tools to support model validation and governance workflows. Demonstrate proficiency with Docker and Kubernetes concerts (e.g., pods, deployments, services, and images) Support and integrate EPLX or similar enterprise platforms into the broader model risk ecosystem. Collaboration & Leadership Partner with cross‑functional teams across the enterprise to address modeling, production, and operational issues. Lead or contribute to projects that support common model risk management strategies. Provide mentorship and guidance to junior team members. Participate in incident triage, perform diagnostics, contribute to root‑cause analysis , and implement corrective or preventative solutions. Required Qualifications: 5+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Strong hands-on experience with Google Cloud Platform (GCP) components: Compute, IAM, Storage, Networking, Monitoring – highly preferred Experience in AWS or Google Cloud Platform (GCP) is acceptable. Candidates with strong AWS backgrounds will be supported and trained to ramp up in GCP. Experience performing python code remediation and modernization during cloud migration efforts, including updating dependencies, restructuring pipelines, and containerizing workloads is highly desired. Demonstrated experience developing python code directly within cloud environments ( GCP and OpenShift ), including during platform migrations. Experience with Kubernetes and container orchestration is expected. Experience with Red Hat OpenShift is a nice to have, and engineers without OpenShift background will be supported in learning it on the job. Proven ability to work inside containerized platforms (pods, operators, CI/CD pipelines) to modify or rebuild application components and automation scripts. Ability to directly troubleshoot and resolve code level issues that surface during GCP or OpenShift migration, deployment, or workload scaling. Proven ability to enter cloud environments and write or re write code, especially during platform modernization or migration efforts. Ability to build, refactor, or optimize code used in production environments and model workflows. Ability to troubleshoot and resolve code level issues arising during cloud deployment, migration, or scaling, including real time diagnostics within GCP or OpenShift consoles. Experience with deployment pipelines (CI/CD) – GitHub, Jenkins, docker, deploying on OpenShift Job Expectations: Ability to travel up to 15% of the time. This position offers a hybrid work schedule. Willingness to work onsite at stated location on the job posting. Job Locations: 401 S Tryon Street, Charlotte, NC 600 S 4th Street, Minneapolis, MN Las Colinas Bldg B, Irving Campus, IRVING, TX West Des Moines Campus, 800 S Jordan Creek Pkwy, WEST DES MOINES, IA D Building,114N Beaumont St -D Bldg., SAINT LOUIS, MO 1150 W Washington, TEMPE, AZ Pay Range Reflected is the base pay range offered for this position. Pay may vary depending on factors incl