CIB Finance Markets Data Engineer - Executive Director

Wells Fargo•New York, NY

1d•$167,000 - $260,000•Hybrid

About The Position

Wells Fargo is seeking a Senior Lead Analytics Consultant to join the CIB Finance Analytics & Insights team. The role leads the design and execution of enterprise-scale data, analytics, and AI solutions that enable faster decision-making across Corporate & Investment Banking Finance. It serves as a strategic leadership role spanning data acquisition, engineering, governance, curation, analytics enablement, and AI adoption, working across Finance, Technology, Data Management, and business stakeholders to establish trusted data foundations, modernize reporting ecosystems, and deploy AI-powered solutions. The position leads cross-functional teams and enterprise data transformation programs; establishes reusable, governed data assets and analytical products; modernizes reporting through cloud platforms, automation, and self-service analytics; and advances responsible generative AI, machine learning, and Copilot use in Finance. It also influences senior leaders on strategic data and AI initiatives and ensures compliance with enterprise governance, risk, security, regulatory, and compliance standards. The role is based at 150 E 42nd Street in New York, NY, and offers a hybrid work schedule. It requires willingness to work onsite at the stated location and is not eligible for visa sponsorship. The annual base pay range is $167,000 to $260,000; employees may also be eligible for incentive opportunities.

Requirements

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 onsite at the stated location; the position has a hybrid work schedule.
Strong communication skills and ability to simplify complex technical concepts for executive audiences.
Ability to influence senior executives and translate business strategy into scalable data and technology solutions.

Nice To Haves

7+ years designing and implementing enterprise data solutions, including data engineering, data warehousing, data management, or analytics platforms.
5+ years building and optimizing ETL/ELT pipelines using SQL, Python, Spark, or comparable technologies.
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 improve productivity.
Experience establishing data governance frameworks, metadata standards, lineage practices, and data quality controls.
Understanding of Finance, Banking, Capital Markets, Client Profitability, or Risk reporting data domains.
Experience leading enterprise-scale data transformation, reporting modernization, or AI adoption initiatives.
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 supporting Finance, Markets, Banking, and enterprise reporting.
Establish and govern reusable data assets through data sourcing, procurement, integration, quality controls, lineage, metadata management, and business definitions.
Develop strategies to modernize legacy reporting through cloud-based data platforms, automation, and self-service analytics.
Partner with Technology and Data Management teams to define the enterprise data model and centralized data products as a single source of truth.
Identify opportunities to reduce manual work through workflow automation, AI-enabled solutions, and intelligent data engineering.
Lead adoption and responsible use of generative AI, machine learning, and Copilot capabilities for Finance reporting, analysis, reconciliations, documentation, and decision support.
Build AI-ready data foundations through 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.
Drive development of enterprise analytical products, data marts, and reusable datasets for 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 enterprise data transformation programs.
Ensure adherence to enterprise data governance, risk management, security, compliance, and regulatory standards.
Fulfill applicable risk program responsibilities, follow Wells Fargo policies and procedures, escalate and remediate issues, and make sound risk decisions.