Lead Risk Analytics Consultant - Data Architecture & BI Enablement

Wells Fargo & Company•Charlotte, NC

22h•Hybrid

About The Position

Wells Fargo is seeking a Lead Risk Analytics Consultant - Data Architecture & Self-Service BI Enablement lead to join IDeAS (Information Delivery and Analytics Solutions). IDeAS designs, delivers, and governs the Risk Platform, enabling consistent, scalable reporting, risk oversight, and advanced analytics across the firm. In this role, you will focus on enabling self-service analytics at scale, not building reports or dashboards. You will design curated datasets and semantic data layers that empower business users, analysts, and BI developers to independently create reporting solutions using Tableau, and Power BI.

Requirements

5+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Nice To Haves

Experience with Microsoft Fabric (Lakehouse, Direct Lake, semantic models)
Strong SQL, Power BI knowledge, with emphasis on leveraging semantic models and curated datasets rather than report/dashboard development
Proven ability to design data solutions that eliminate manual data pulls and reduce dependency on centralized reporting teams
Experience working with large-scale datasets, and Parquet file structure
Excellent communication, organizational, and planning skills
Experience in collaborating with both technical and non-technical partners with a problem-solving mindset
Experience in Capital Markets and Risk Management

Responsibilities

Drive scalable, self-serve BI solutions that deliver actionable insights and business value through advanced analytics, and automation to make actionable insights, trends, recommendations, or contribute to large-scale planning that has a broader impact
Enable self-service curated datasets and semantic layers for business stakeholders.
Define and maintain semantic models, data dictionaries, and KPIs
Lead data consolidation and rationalization across a complex ecosystem, transforming hundreds of disparate source tables into curated, governed, and business-ready datasets that minimize redundancy and eliminate manual data pulls
Own the end-to-end data consumption architecture, defining how curated datasets, semantic models, and data access layers are structured and integrated with BI tools and AI-driven query interfaces
Provide hands-on enablement and training to business stakeholders and BI users in Power BI, focusing on how to effectively use curated datasets and semantic models
Partner with Technology teams to implement scalable pipelines and datasets in Microsoft Fabric (Lakehouse)
Design datasets for high-performance consumption across large-scale data volumes (millions to billions of rows)
Act as the primary business-side architectural counterpart to the Technology execution team building data models and pipelines
Provide clear execution artifacts, including dataset specifications, mapping logic, acceptance criteria, test scenarios, and performance targets.