Lead Data Product Management Consultant - Customer Information Management

Wells Fargo Bank•Charlotte, NC

1d•Hybrid

About The Position

Wells Fargo is seeking a Lead Data Product Management Consultant to join the Customer Data Products (CDP) group within Digital Data & Artificial Intelligence (DDAI) as part of Consumer Banking & Lending (CBL). Our vision is to create a ‘Know Me’ experience for our customers by enabling Wells Fargo products and customer journeys to quickly obtain high-quality customer information. Our product areas introduce new capabilities and modernize legacy platforms to improve customer data quality and enable enterprise agility. Customer Information Management (CIM) is a mission-critical data product that maintains and delivers accurate and timely core customer profile data across firmwide channels. The Senior Lead Digital Product Manager is responsible for building strategy & requirements for digital platforms and properties to achieve business outcomes.

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

4+ Years in Agile methodology experience
3+ years of experience in one or more of the following functional areas: large enterprise platforms and complex implementations, business technology solutions, or event-driven architecture, with a clear track record of building innovative, customer-facing capabilities
Previous experience working with JIRA (creating features/epics/user stories)
Experience working in one or more of the following customer data sub-domains: identity, relationships, communication methods, preferences, privacy.
Demonstrated experience with data governance standards
Proven ability to work within a product team
Strong interpersonal and communication skills
Strong analytic background
Proven ability to engage and work with technology partners
Data product management or project management withing Financial Services industry
Working understanding of Hogan CIS
Understanding of modernized microservices including MongoDB, Kafka, and APIs

Responsibilities

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 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 workstream 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
Support the Customer Information Management - Customer Relationships (CR) Product scrum teams to deliver product features and functions to meet prioritized enterprise objectives
Assist defining, measuring and tracking product OKRs and key performance indicators and business value (revenue gains, efficiency saves, etc.)
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