Data Product Management Lead

TransUnion•White Plains, NY

1d•$100,100 - $150,000•Hybrid

About The Position

This role will report to a Director of Data Asset Management. As an Advisor, Data Enablement, you will serve as a senior data product manager responsible for the strategy, structure, and performance of prioritized credit and non-credit data domains. This role plays a critical part in ensuring that data across the organization is discoverable, understandable, and trusted enabling maximum value realization across products, analytics, and business operations. You will act as the subject matter expert (SME) for your assigned data domains, owning their full lifecycle from onboarding and standardization to optimization, enhancement, and sunset. You will ensure that all contributing data sources are centralized and aligned to consistent standards, enabling scalable and reliable use across internal stakeholders. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Requirements

Bachelor’s degree in management, economics, finance or a related field
10+ years of progressive experience in data, product management, analytics, or related roles
Demonstrated experience owning product strategy, roadmap, and delivery outcomes
Proven ability to influence senior stakeholders and drive alignment in a layered environment with experience working across business, technical, and analytics teams at scale
Driven by intellectual curiosity and independent thinking with a positive “can do” attitude

Responsibilities

Develop a deep, hands-on understanding of assigned data domains, including underlying data sources, structures, and business use cases.
Serve as the primary owner and SME for assigned credit and non-credit data domains, ensuring alignment with business priorities and strategic objectives.
For new data domains, design and define data schemas for ingestion and storage, ensuring scalability, consistency, and usability across systems.
Monitor data domains for quality, completeness, and consistency, identifying gaps and opportunities for improvement.
Establish data quality standards, SLAs, and KPIs for assigned data domains
Partner with data users to ensure data remains relevant, understandable, and effective for its intended purposes.
Develop a strong understanding of how data is used in downstream processes, analytics, and products, and identify opportunities to maximize value.
Lead decisions to enhance, replace, or sunset data assets as business needs evolve and drive associated impact assessments, stakeholder alignment, and communication strategies.
Act as a connector between DAM, Solutions, and GT, translating requirements into structured data solutions.