CIB Finance Markets Data Engineer - Executive Director

Wells Fargo Bank•Charlotte, NC

15h•$139,000 - $260,000•Hybrid

About The Position

Wells Fargo is seeking a Senior Lead Analytics Consultant to join the CIB Finance Analytics & Insights team. This role leads the design and execution of enterprise-scale data, analytics, and AI solutions to enable faster decision-making across Corporate & Investment Banking Finance. The successful candidate serves as a strategic leader for data acquisition, engineering, governance, curation, analytics enablement, and AI adoption, partnering across Finance, Technology, Data Management, and business stakeholders. The role establishes trusted data foundations, modernizes reporting ecosystems, and deploys AI-powered solutions to improve productivity, insight generation, and operational efficiency. It leads scalable data architectures, pipelines, curated datasets, enterprise analytical products, data marts, and reusable datasets for Finance, Markets, Banking, executive reporting, planning, client analytics, profitability analysis, and strategic decisions. The position also drives responsible adoption of generative AI, machine learning, and Copilot capabilities, builds AI-ready data foundations, and sets practices for prompt engineering and reusable AI workflows. This position has a hybrid work schedule and requires willingness to work on-site at the stated location. It is not eligible for visa sponsorship. Posting locations are Charlotte, North Carolina, and San Francisco, California. The base pay range is $139,000–$217,000 annually for Charlotte and $167,000–$260,000 annually for San Francisco; pay may vary based on performance, skills, experience, and work location. Employees may also be eligible for incentive opportunities.

Requirements

At least 7 years of Analytics, Reporting, Financial Modeling, or Statistics experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination.
Willingness to work on-site at the stated location; the position follows a hybrid work schedule.
Not eligible for visa sponsorship.

Nice To Haves

At least 7 years designing and implementing enterprise data solutions, including data engineering, data warehousing, data management, or analytics platforms.
At least 5 years building and optimizing ETL/ELT pipelines using SQL, Python, Spark, or comparable technologies.
At least 5 years leading large-scale data sourcing, integration, cleansing, and data quality initiatives across multiple systems.
Experience with modern cloud data platforms such as Microsoft Fabric, Azure, Snowflake, Databricks, or equivalent technologies.
Advanced SQL and data modeling expertise, including dimensional modeling, performance optimization, and data architecture design.
Experience delivering analytics insights for CIB Markets businesses, including Equities, Rates, FX, Commodities, Structured Products, and Municipal Securities.
Experience implementing AI-enabled analytical solutions using generative AI platforms, LLMs, machine learning, or intelligent automation technologies.
Experience developing and governing enterprise semantic models, curated datasets, data marts, or data products.
Experience developing reusable AI workflows, prompt frameworks, AI skills, or automation capabilities that materially improve productivity.
Experience establishing data governance frameworks, metadata standards, lineage practices, and data quality controls.
Strong understanding of Finance, Banking, Capital Markets, Client Profitability, or Risk reporting data domains.
Proven ability to lead enterprise-scale initiatives involving data transformation, reporting modernization, or AI adoption.
Experience influencing senior executives and translating business strategy into scalable data and technology solutions.
Strong communication skills and demonstrated ability to simplify complex technical concepts for executive audiences.
Experience supporting Corporate & Investment Banking Finance organizations.
Experience with Microsoft Fabric, Power BI, Dremio, GitHub Copilot, and Tableau.
Experience building AI-assisted analytics solutions.
Knowledge of financial products, client profitability, capital allocation, funding, treasury, or Markets reporting.

Responsibilities

Lead the design and implementation of scalable data architectures, pipelines, and curated datasets for Finance, Markets, Banking, and enterprise reporting initiatives.
Establish and govern trusted, reusable data assets through data sourcing, procurement, integration, quality controls, lineage, metadata management, and business definitions.
Develop and execute strategies to modernize legacy reporting environments using cloud data platforms, automation, and self-service analytics.
Partner with Technology and Data Management teams to define the enterprise data model and centralized data products serving as a single source of truth for analytical consumers.
Identify opportunities to reduce manual work through workflow automation, AI-enabled solutions, and intelligent data engineering.
Lead responsible adoption of generative AI, machine learning, and Copilot capabilities for reporting, analysis, reconciliations, documentation, and decision support.
Build AI-ready data foundations with data quality, consistency, governance, semantic modeling, and contextual documentation.
Establish best practices for prompt engineering, AI workflow development, reusable AI skills, and responsible AI implementation across analytical teams.
Drive development of enterprise analytical products, data marts, and reusable datasets supporting executive reporting, planning, client analytics, profitability analysis, and strategic decision-making.
Evaluate emerging data and AI technologies and recommend architecture, investment priorities, and implementation roadmaps.
Influence senior leaders across Finance, Technology, Data Management, and business lines to align on strategic data and AI initiatives.
Lead cross-functional teams delivering high-visibility enterprise data transformation programs.
Ensure adherence to enterprise data governance, risk management, security, compliance, and regulatory standards.