Lead Finance Data Management Analyst

Wells Fargo

. Act as a data steward and lead complex data integrity and quality initiatives and reviews of broadly impactful business systems .

Posted 11/3/2026full-timeUnited StatesSenior💰 $100,000 - $179,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data quality management, including the ability to lead initiatives, analyze complex datasets, and ensure compliance with data governance standards. Proficient in SQL, Python, and various data management tools to drive data integrity and quality improvements.

Highest-signal resume keywords

Data Quality ManagementSQL AnalysisPython for Data AnalysisMicrosoft Power PlatformData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Quality StandardsData Integrity InitiativesData Quality AuditsData Quality ControlsRoot-Cause AnalysisData LineageMetadata ManagementFinancial Data PlatformsAgile MethodologiesProject Management

Soft Skills

MentoringCommunicationProblem SolvingCollaborationInfluencing Outcomes

Tools & Technologies

Microsoft Power BIPower AutomatePower AppsAzureGitHubAPIsAI-Enabled SolutionsMicrosoft CopilotWorkflow OrchestrationPerformance Metrics Development

Industry Keywords

Banking ProductsFinancial ProductsRegulatory ComplianceRisk ManagementOperational DataData PrivacyInformation SecurityRecords ManagementModel RiskEnterprise Data Management

Tech Stack

Tools & technologies

AzurePythonSQL

About the role

Key responsibilities & impact

Act as a data steward and lead complex data integrity and quality initiatives and reviews of broadly impactful business systems
Participate in large-scale planning related to data quality improvement and business systems
Review and analyze complex, multi-faceted data quality audits
Research and resolve data quality issues across multiple systems, datasets, and data connections
Make decisions involving data quality standards and control frameworks
Lead review and remediation of data quality issues and drive new initiatives
Collaborate with business, risk partners, technical staff, Enterprise Data Management, and Technology functions to triage and resolve data quality issues
Mentor peers
Ensure compliance with Enterprise Data Management policies, standards, and technology
Facilitate execution of business data standards and control frameworks
Understand the full 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 monitoring approaches
Define strategies and identify critical data elements and data quality rules
Advise senior management on current-state data and metadata quality assessments

Requirements

What you’ll need

5+ years of data quality or data management experience, or equivalent demonstrated through work experience, training, military experience, or education
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
Experience independently managing moderately complex projects, initiatives, or workstreams
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
Must work at one of the specified Charlotte, North Carolina or Minneapolis, Minnesota locations under the hybrid schedule
Not eligible for visa sponsorship

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement
Incentive opportunities may be available