Lead Finance Data & Application Consultant

Remote Full-time
About the position

Wells Fargo is seeking a Lead Finance Data & Application Consultant to join our Finance team. This position requires strong information systems experience combined with sound business and reporting acumen. This role sits within the Finance Transformation Office, with a primary focus on enterprise management reporting. The ideal candidate will have the ability to interpret banking financial statements and support applications that enable internal performance reporting across the lines of business. As part of a transformation-focused organization, this role requires mastering legacy reporting applications while helping transition existing use cases to modern technology platforms. Success in this function depends on the ability to collaborate effectively with finance stakeholders across the enterprise, translate requirements into actionable deliverables, and support the development of scalable, future‑ready solutions. This position offers a unique opportunity to build a broad enterprise financial perspective while gaining hands-on experience with modern analytical and data technologies. In this role, you will: Lead complex data product initiatives, including enterprise-wide efforts with cross-functional impacts, to drive data enablement and capability enhancement across platforms and utilities. Review and analyze multi-faceted, large-scale, or long‑term data product initiatives that require deep evaluation of multiple factors—including intangible and unprecedented considerations—to support data enablement strategies and roadmaps aligned with governance standards. Make decisions in complex scenarios by applying strong knowledge of data, analytics, and integration requirements, informing prioritization, solution architecture, and roadmap development while guiding teams toward successful delivery. Collaborate strategically with peers, colleagues, and mid‑ to senior-level leaders to ensure data product solutions are designed for optimal performance, support analytics across multiple platforms, and resolve data‑related issues; may lead projects, mentor peers, or guide workstreams. Provide strategic input on use case intake, prioritization decisions, and product roadmap development, contributing to key business processes and planning activities. Manage complex datasets with a strong focus on end‑user needs and business objectives, maintaining alignment with established data governance practices. Create and maintain data product roadmaps throughout the product life cycle, including detailed specifications, requirements, and process flows. Design and maintain innovative data products that enable data availability for business intelligence, analytics, and reporting. Serve as a strategic liaison between data management, product teams, data engineering, and architecture partners across the full data product lifecycle.

Responsibilities
• Lead complex data product initiatives, including enterprise-wide efforts with cross-functional impacts, to drive data enablement and capability enhancement across platforms and utilities.
• Review and analyze multi-faceted, large-scale, or long‑term data product initiatives that require deep evaluation of multiple factors—including intangible and unprecedented considerations—to support data enablement strategies and roadmaps aligned with governance standards.
• Make decisions in complex scenarios by applying strong knowledge of data, analytics, and integration requirements, informing prioritization, solution architecture, and roadmap development while guiding teams toward successful delivery.
• Collaborate strategically with peers, colleagues, and mid‑ to senior-level leaders to ensure data product solutions are designed for optimal performance, support analytics across multiple platforms, and resolve data‑related issues; may lead projects, mentor peers, or guide workstreams.
• Provide strategic input on use case intake, prioritization decisions, and product roadmap development, contributing to key business processes and planning activities.
• Manage complex datasets with a strong focus on end‑user needs and business objectives, maintaining alignment with established data governance practices.
• Create and maintain data product roadmaps throughout the product life cycle, including detailed specifications, requirements, and process flows.
• Design and maintain innovative data products that enable data availability for business intelligence, analytics, and reporting.
• Serve as a strategic liaison between data management, product teams, data engineering, and architecture partners across the full data product lifecycle.

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

Nice-to-haves
• Demonstrated experience with core banking concepts, including liquidity management, capital frameworks, balance sheet yield analysis, and funds transfer pricing
• Ability to accurately interpret outputs from accounting information systems and general ledger platforms
• Proficiency in analytic and reporting tools such as Essbase, SQL, Power BI, or comparable technologies
• Strong aptitude for emerging technologies, including Artificial Intelligence, with the ability to leverage AI to drive process efficiencies
• Proven ability to lead change initiatives, manage competing priorities, communicate deliverables clearly, and establish realistic timelines
• Skilled in translating complex financial and technical topics into clear, understandable communications for broad audiences
• Ability to utilize Jira for project and workflow tracking
• Experience supporting daily, monthly, and quarterly reporting cycles
• Strong collaboration skills with internal risk, compliance, and control partners
• Ability to follow established control processes and integrate new control requirements into existing and future applications
• Demonstrated capability to identify automation, simplification, and optimization opportunities across legacy and emerging processes

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