Senior Lead Data Product Management Consultant -- Auto Data & Insights

Wells Fargo•Irving, TX

21h•Hybrid

About The Position

Wells Fargo is seeking a Sr. Lead Data Product Management Consultant to join their Auto business. This product-focused role will shape and drive the strategy, roadmap, and delivery of enterprise data products that support operational processes, analytics, regulatory reporting, and strategic business initiatives. The individual will partner with business stakeholders to identify needs, define measurable outcomes, translate priorities into executable features and user stories, and guide cross-functional teams from discovery through implementation and adoption. A strong understanding of data engineering, data models, pipelines, and platform capabilities is needed to evaluate feasibility, challenge proposed solutions, manage dependencies, and ensure products are scalable, governed, and fit for purpose; however, the role is accountable for driving the work from the product side rather than performing hands-on engineering development. Success in this role requires a product mindset, strong ownership, and the ability to connect business outcomes with technical delivery. The ideal candidate can establish a clear product vision, manage intake and prioritization, maintain a delivery-ready backlog, and influence business, data engineering, architecture, governance, and control partners. Data engineering experience or fluency is important for understanding source-to-consumption data flows, assessing solution options, anticipating delivery risks, and helping teams make sound product and technical trade-offs.

Requirements

7+ 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

Strong product management capabilities, including product vision, roadmap development, use case intake, prioritization, backlog management, outcome definition, and lifecycle ownership.
Experience in auto lending, consumer lending, or financial services.
Working knowledge of data engineering concepts, including data modeling, data pipelines, data integration, APIs, ETL/ELT, streaming, data warehouses, and cloud or modern data platforms.
Demonstrated experience leading data products, platforms, or large-scale data initiatives from strategy and discovery through delivery and adoption.
Experience translating complex business and regulatory needs into epics, features, user stories, acceptance criteria, and executable delivery plans.
Ability to partner effectively with data engineers and architects, understand technical constraints, evaluate solution trade-offs, and drive decisions without needing to be the primary developer.
Strong stakeholder management, communication, facilitation, and influencing skills across business, technology, risk, control, and senior leadership partners.
Ability to navigate ambiguity, create clarity, manage competing priorities, and drive accountability in a fast-paced, cross-functional environment.
Fluency in agile product delivery practices, including product discovery, backlog refinement, sprint or Kanban planning, release readiness, and continuous improvement.

Responsibilities

Own and communicate the vision, strategy, and roadmap for Auto Finance data products.
Lead product discovery with stakeholders to define problems, user needs, target outcomes, success measures, and minimum viable product scope before work enters delivery.
Translate business needs into clear epics, features, user stories, acceptance criteria, and product requirements that enable data engineering and delivery teams to execute effectively.
Serve as the product lead and strategic liaison across business, data engineering, architecture, data management, analytics, operations, risk, and control partners throughout the product lifecycle.
Use knowledge of data models, pipelines, integration patterns, data warehouses, and platform capabilities to assess technical options, challenge assumptions, and guide scalable product solutions.
Partner with engineering and architecture teams on target-state designs for new data sources and reusable data products without serving as the hands-on solution engineer.
Ability to use SQL to investigate data, validate assumptions, assess data quality, and support product decisions
Define and monitor product outcomes and service measures, including adoption, quality, timeliness, reliability, compliance, and business value.
Drive timely decisions, remove delivery barriers, escalate risks, and align stakeholders when priorities, requirements, or technical constraints conflict.