Lead data management analyst

About this role:

Wells Fargo is seeking for a candidate who is responsible for overseeing enterprise data governance, quality and integrity initiatives. The candidate should collaborate with the business and technology partners to ensure the data is accurate, consistent, accessible and aligned with business needs. the role combines deep technical skills, strategic thinking, cross functional leadership and hands-on problem solving.

In this role, you will:

• Organize and lead complex companywide initiatives to ensure that data quality is maintained so that data can effectively support business processes
• Oversee analysis and reporting in support of regulatory requirements
• Identify and recommend analysis of data quality or integrity issues
• Evaluate data quality metrics and data quality audits to benchmark the state of data quality
• Make decisions in complex and multi-faceted situations requiring solid understanding of data governance standards and procedures
• Identify new data sources and develop recommendations for assessing the quality of new data
• Lead project teams and mentor less experienced staff members
• Recommend remediation of process or control gaps that align to management strategy
• Serve as relationship manager for a line of business
• Consult with and provide recommendations to senior management regarding assessments of the current state of data and metadata quality within area of assigned responsibility
• Represent client in cross-functional groups to develop companywide data governance strategies
• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to coordinate and drive collaboration on solution design and remediation execution

Required Qualifications:

• 7+ years of Data Management, Business Analysis, Analytics, or Project Management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Lead efforts through phases of a large enterprise project; requirements, design, implementation, testing, and end-state product management
• Lead complex data product initiatives, including those that are cross-functional with broad impact, and act as key participant in large-scale planning driving data enablement and capabilities across platforms and utilities
• Review and analyze complex multi-faceted, larger scale or longer-term data product initiatives that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors to drive data enablement strategies and roadmaps, while adhering to set data governance and standards
• Make decisions in complex and multi-faceted situations requiring solid understanding of data, analytics, and integration needs of line of business partners to inform prioritization, roadmap, and architecture design, that influence and lead broader work team to meet deliverables and drive new initiatives
• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to ensure data product solutions are built for optimal performance and design analytics applications across multiple platforms, resolve data product issues, and achieve goals; may lead projects, teams or serve as a peer mentor
• Provide strategic input on new use case intake, prioritization, product roadmap definition, and other critical business processes
• Manage complex datasets continuously focusing on the consumers of the data and their business needs, while adhering to set data governance
• Create and maintain data product roadmaps throughout the data product life cycle with detailed specifications, requirements, and flows for data capabilities
• Design and maintain innovative data products, enabling data availability for data intelligence, analytics, and reporting
• Serve as a strategic liaison between data management, product teams, data engineering, and architecture teams throughout the data product life cycle
• Skills: SQL - Teradata, Snowflake Python, Regression & Clustering, Alteryx & LLM

Job Expectations:

• Lead development and implementation of data management strategies across business units.
• Ensure consistent data definition and usage across systems.
• Mentor and guide data analysts, enforcing best practices in data handling
• Collaborate with data engineers and architects to optimize data flow and storage.
• Oversee processes for data profiling, validation, cleansing and enrichment
• Identify, investigate and resolve data quality issues through root cause analysis
• Support data integration efforts and data architecture review