Data Product Manager

JPMorgan Chase & Co.•Jersey City, NJ

5h•$133,000 - $215,000

About The Position

As a Data Product Manager at JPMorganChase within Employee Platforms, you will lead the discovery, design, and delivery of data products that enable smarter workflows, better decisions, and measurable operational outcomes. You will serve as the connective tissue between business stakeholders, data engineering, and governance teams — translating complex workflow needs into governed, reusable data assets. This is a high-impact role for someone who thrives in ambiguity, brings structure to complexity, and is passionate about building data products that people actually use.

Requirements

Formal training or certification on product engineering concepts and 5+ years applied experience
Demonstrated experience in data product management, analytics product management, or product management for data and analytics platforms in a complex enterprise environment
Proven ability to gather requirements from stakeholders and translate them into deliverable roadmaps, backlogs, and measurable outcomes
Experience analyzing workflows and defining key performance indicators and metrics that support decisioning and operational improvement
Experience working within data governance frameworks in a multi-domain enterprise, including definitions, ownership and stewardship, lineage and metadata, data quality, and change control
Strong cross-functional collaboration skills with engineering, product, operations, and governance and control partners
Strong written and verbal communication skills with the ability to tailor messaging for diverse audiences

Nice To Haves

Experience with human resources, employee platforms, or internal enterprise platforms supporting large-scale employee workflows
Familiarity with modern data architectures such as warehouse and lakehouse patterns, semantic and metrics layers, and business intelligence enablement patterns
Experience supporting controlled reporting and data quality frameworks in regulated environments
Exposure to privacy-by-design principles and responsible data handling practices in environments involving personal information

Responsibilities

Partner with business stakeholders to understand workflow goals, pain points, decision points, and operational constraints; translate needs into clear product requirements and user stories
Analyze stakeholder workflows end-to-end — including process steps, handoffs, decision points, exceptions, and control touchpoints — to identify opportunities for automation, standardization, and data-driven decision making; define key performance indicators and success measures
Define data domain concepts (entities, events, and measures) required to support priority workflows; document business definitions and metric logic to enable reuse and consistency across teams
Collaborate with data engineering and platform teams to deliver curated datasets and governed metrics layers, including documentation, data quality expectations, lineage and metadata inputs, and access patterns
Apply and reinforce data governance practices across a multi-domain enterprise, including definition alignment, ownership and stewardship support, data quality management, metadata documentation, and change control; escalate issues and drive resolution through appropriate forums
Drive product adoption through enablement activities such as training, documentation, and office hours; embed analytics into operating rhythms and track usage and outcomes
Manage product lifecycle processes including backlog management, prioritization, releases, and deprecation; support operating model execution aligned with risk and control expectations
Ensure communications about metrics, reporting, and analytics are accurate, clear, and appropriate for intended audiences and channels