Data Product Integrity Specialist

Wells Fargo is seeking a Data Product Integrity Specialist

In this role, you will:

• Act as a data steward; participate in low to moderate complexity data integrity and quality initiatives and reviews of business systems; identify opportunities for process improvement with business systems
• Review and analyze basic data quality audits with low to moderate risk; research and resolve data quality issues related to systems, data sets and data connections
• Present recommendations for resolving low to moderate complexity data quality issues and exercise independent judgment while developing expertise in the data quality standards and control framework; escalate and remediate low to moderate complexity data quality issues
• Collaborate and consult with business, risk partners, and technical staff, including Enterprise Data Management and Technology functions, to triage and remediate data quality issues
• Ensure compliance with Enterprise Data Management policies, standards, and technology and facilitate execution of business data standards and control frameworks
• Understand the complete data lifecycle from data creation and capture to data processing, storage, and usage
• Identify and track end-to-end data lineage using traditional methods and systemic tools
• Actively engage in identifying solutions to improve data and implement data quality improvement plans

• 2+ years of data quality or data management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• 2+ years of data quality, data analysis, or data management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, or education
• Experience with data defects, data-quality controls, reconciliations, production support, issue management, or root-cause analysis.
• Knowledge of banking or financial products and Finance, accounting, general ledger, regulatory, risk, or operational data.
• 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.
• Working knowledge of SQL, including querying, joining, aggregating, reconciling, and analyzing structured data.
• Demonstrated ability to investigate data discrepancies, identify patterns, document findings, and reach supportable conclusions.
• Ability to communicate technical or data-related findings clearly in written and verbal form.
• 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.
• The Finance Data Management Office is seeking a Data Product Integrity Specialist to support defect management within Finance Data Operations.
• The position will analyze data-quality concerns, support the resolution of defects, and help ensure that data used by Finance is complete, accurate, timely, and fit for its intended purpose.The analyst will work with Finance, Operations, Technology, data providers, product teams, and data consumers to research issues, document impacts, identify ownership, and track remediation.
• This is an analytical role requiring SQL capability, sound judgment, attention to detail, and an interest in financial products and data

• 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.