Finance Data Management Analyst

Wells Fargo•Minneapolis, MN

2d•$68,000 - $114,000•Hybrid

About The Position

Wells Fargo is seeking a Data Management Analyst to support defect management within Finance Data Operations. The analyst will investigate data-quality concerns, support defect resolution, and help ensure Finance data is complete, accurate, timely, and fit for its intended purpose. The role works with Finance, Operations, Technology, data providers, product teams, and data consumers to research issues, document impacts, identify ownership, and track remediation. The position offers a hybrid work schedule at either 11625 N. Community House Road, Charlotte, NC 28202, or 550 S. 4th Street, Minneapolis, MN 107935. Relocation assistance is unavailable, and the role is not eligible for visa sponsorship. Specific compliance policies may apply to outside activities or personal investing; affected employees must provide information to the Wells Fargo Personal Account Dealing Team and follow applicable policies. Employees are also accountable for following risk and compliance programs, escalating and remediating issues, and making risk decisions consistent with company requirements.

Requirements

At least 2 years of data quality, data analysis, or data management experience, or equivalent demonstrated through work experience, training, military experience, or education.

Nice To Haves

At least 1 year of SQL experience, including querying, joining, aggregating, reconciling, and analyzing structured data.
Knowledge of banking or financial products and Finance, accounting, general ledger, regulatory, risk, or operational data.
Ability to investigate data discrepancies, identify patterns, document findings, and reach supportable conclusions.
Ability to communicate technical or data-related findings clearly in writing and verbally.
Ability to use current AI and productivity tools, including Microsoft Copilot, and validate AI-assisted outputs before using them in analysis, documentation, or reporting.
Ability to manage assigned work, maintain accurate records, meet deadlines, and escalate risks or impediments appropriately.
Experience with data defects, data-quality controls, reconciliations, production support, issue management, or root-cause analysis.
Experience profiling or validating large datasets.
Understanding of data-quality concepts, including completeness, accuracy, timeliness, validity, consistency, and reconciliation.
Familiarity with JIRA, ServiceNow, data-quality platforms, workflow tools, or similar issue-management applications.
Experience preparing defect metrics, dashboards, trend reporting, or management information.
Familiarity with Python, Power BI, automation tools, or AI-assisted data analysis.
Understanding of data lineage, metadata, source-to-target mapping, or data transformation.
Experience working with India- and US-based stakeholders in a global operating model.

Responsibilities

Participate in low-to-moderate complexity data-quality and defect-management initiatives.
Analyze data-quality control failures, reconciliation exceptions, production issues, and reported data concerns using SQL and other analytical tools.
Research issues across the data lifecycle to identify affected data, potential root causes, business impacts, and accountable parties.
Manage assigned defects from intake and triage through remediation tracking, validation, evidence collection, and closure.
Support the execution, analysis, and enhancement of data-quality rules, controls, tactical adjustments, and remediation solutions.
Maintain complete and accurate defect records, status information, supporting documentation, and management reporting.
Prepare defect metrics and trend analysis to identify recurring issues, aging items, remediation barriers, and matters requiring escalation.
Communicate findings clearly to business and technical stakeholders and collaborate with partners to support timely resolution.
Use approved AI tools, including Microsoft Copilot, to improve research, analysis, documentation, and productivity while validating outputs before business use.
Identify opportunities to improve or simplify defect-management processes through standardization, reporting, and automation.
Follow applicable Wells Fargo policies and procedures, fulfill risk and compliance obligations, and escalate and remediate issues appropriately.