Lead Finance Data Management Analyst

Wells Fargo•Minneapolis, MN

2d•$100,000 - $179,000•Hybrid

About The Position

The Finance Data Management Office is seeking a Lead Data Management Analyst to support defect management within Finance Data Operations. The position analyzes data-quality concerns, supports defect resolution, and helps ensure Finance data is complete, accurate, timely, and fit for its intended purpose. The analyst works with Finance, Operations, Technology, data providers, product teams, and data consumers to research issues, document impacts, identify ownership, and track remediation. The role acts as a data steward and leads complex data-integrity and quality initiatives, audits, reviews, and remediation efforts with broad business impact. It requires end-to-end knowledge of the data lifecycle and lineage, application of data-quality standards and control frameworks, and development of improvement plans, monitoring approaches, critical data elements, and quality rules. The analyst collaborates with business, risk, and technical teams, mentors peers, and provides senior management with recommendations on the state of data and metadata quality. The position offers a hybrid work schedule from either the Charlotte, North Carolina or Minneapolis, Minnesota location listed in the posting. Relocation assistance is not available, and the position is not eligible for visa sponsorship.

Requirements

5+ years of data quality or data management experience, or equivalent demonstrated through work experience, training, military experience, or education.

Nice To Haves

4+ years of SQL experience analyzing structured, high-volume, or complex datasets.
Knowledge of banking or financial products and Finance, accounting, regulatory, risk, control, or operational data.
Experience using Python for data analysis, reporting, process automation, workflow development, or solution prototyping.
Experience using and developing AI-enabled solutions with tools such as Microsoft Copilot, agents, reusable skills, prompts, or workflow orchestration to support analysis, research, process improvement, or operational efficiency.
Experience independently managing moderately complex projects, initiatives, or workstreams involving multiple stakeholders, competing priorities, dependencies, risks, and deliverables.
Ability to analyze ambiguous business or data problems and develop structured recommendations or solution options.
Ability to communicate technical concepts, recommendations, risks, and status clearly to business and technical stakeholders.
Experience with Microsoft Power Platform, Power Automate, Power Apps, Power BI, Azure, GitHub, APIs, or equivalent technologies.
Experience translating operational needs into requirements, user stories, prototypes, process designs, or implementation roadmaps.
Experience with data-quality controls, reconciliations, defect and issue management, root-cause analysis, production support, financial-data platforms, or operational reporting.
Knowledge of responsible AI, data privacy, information security, access management, records management, model risk, or controls applicable to automated solutions.
Experience developing dashboards, performance metrics, management information, or benefit-measurement frameworks.
Understanding of data lineage, metadata, data architecture, source-to-target transformations, or enterprise data governance.
Experience working in Agile, product-management, or structured technology-delivery environments.
Experience influencing outcomes across India- and US-based Operations and Technology teams without direct authority.

Responsibilities

Act as a data steward and lead complex data integrity and quality initiatives and reviews of business systems with broad impact.
Participate in large-scale planning related to data quality improvement and business systems.
Review and analyze complex, multifaceted data-quality audits; research and resolve issues requiring evaluation of multiple systems, datasets, and data connections.
Make decisions in complex situations using a solid understanding of data-quality standards and control frameworks.
Influence and lead the review and remediation of data-quality issues to meet deliverables and drive new initiatives.
Collaborate and consult with business, risk partners, and technical staff, including Enterprise Data Management and Technology, to lead, triage, and resolve data-quality issues.
Serve as a mentor for peers.
Ensure compliance with Enterprise Data Management policies, standards, and technology, and facilitate execution of business data standards and control frameworks.
Understand the data lifecycle from creation and capture through processing, storage, and usage.
Serve as an expert on end-to-end data lineage using traditional methods and systemic tools.
Create data-quality improvement plans and set approaches for monitoring data quality to maximize efficiency and minimize risk.
Define strategies and identify critical data elements and data-quality rules to govern business data effectively.
Consult with senior management and provide recommendations regarding assessments of current data and metadata quality within the assigned area.