Data Product Manager

About this role

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT. The Technical Data Product Manager will own enterprise data products that support business decision-making, operational efficiency, and regulatory compliance. This role operates at the intersection of business, data engineering, architecture, analytics, and governance. The Technical Data Product Manager will translate business needs into scalable, trusted data products while using strong technical and analytical judgment to investigate issues, validate business logic, and make informed product decisions. Advanced SQL and data analysis are central to the role, and this person must be able to independently work with complex datasets while partnering effectively with engineering, architecture, analytics, and governance teams. What you will do: • Own the roadmap, priorities, delivery, and ongoing management of assigned enterprise data products or components of a data domain.

• Develop a strong understanding of how assigned data products are sourced, transformed, governed, and consumed, and use that understanding to identify opportunities to improve reliability, usability, quality, and business value.

• Use SQL regularly to investigate data questions, validate business logic, analyze data across multiple tables, trace discrepancies, and independently assess whether data products are producing expected results.

• Troubleshoot data quality issues by identifying where problems originate, evaluating downstream impact, and partnering with the appropriate technical and business teams to drive resolution.

• Translate business, analytical, operational, and regulatory needs into clear product requirements that engineering and analytics teams can execute.

• Define and maintain product requirements, epics, user stories, and supporting documentation for datasets, metrics, APIs, dashboards, and related data capabilities.

• Partner with data engineering and architecture teams on data models, pipelines, interfaces, dependencies, and architecture decisions. Understand the technical design well enough to ask informed questions, evaluate tradeoffs, and represent the product and business impact of those decisions.

• Work through situations where business definitions, source data, technical constraints, and governance requirements do not initially align. Bring the right stakeholders together, clarify tradeoffs, and drive decisions.

• Incorporate data quality, metadata, lineage, master data management, access, privacy, retention, and other governance requirements into product decisions and delivery.

• Ensure data products meet established expectations for quality, performance, availability, scalability, security, and usability.

• Support regulatory, risk, and audit reviews by helping explain how data is sourced, transformed, controlled, accessed, and used.

• Track and report on data product usage, quality, delivery performance, and other measures of product health.

• Drive adoption through clear documentation, stakeholder communication, and enablement.

• Work within Agile delivery practices while balancing roadmap priorities with data issues, regulatory requirements, stakeholder needs, and changing business priorities.

• During the first 6 to 12 months, establish clear priorities for assigned data products, build a working understanding of their data flows and dependencies, identify meaningful quality or usability gaps, and strengthen how the products are delivered, governed, measured, and used.

What you will bring: • Bachelor’s degree in computer science, engineering, business, or a related field.

• 5 to 7+ years of product management experience, including experience with data, analytics, or platform products.

• Advanced SQL and data analysis capability demonstrated through hands-on work with complex datasets. You should be able to independently write and interpret complex joins across multiple tables, trace data through transformations, validate business logic, reconcile conflicting results, and investigate data quality issues without relying entirely on engineering or analytics partners.

• Demonstrated experience using SQL to solve a meaningful business or product problem, such as identifying the source of an incorrect metric, validating data transformations, comparing results across systems, investigating a data defect, or determining whether delivered data met an intended business need.

• Ability to use SQL and data analysis as part of product decision-making, including testing assumptions, validating requirements, investigating defects, and assessing whether delivered data supports the intended outcome.

• Demonstrated ownership of a data product, data capability, or meaningful component of a data domain from business need through delivery and ongoing use. You should be able to explain what you personally owned, the decisions you made, and how you evaluated whether the product was successful.

• Demonstrated experience working with data engineers and architects on data models, pipelines, or architecture decisions. You should be able to explain a technical or delivery tradeoff you influenced and the effect of that decision.

• Demonstrated experience translating an ambiguous busi

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