Data Product & Governance Lead

Thanks to our commitment to creating a supportive and engaged workplace culture, Gorilla Glue has been recognized as a top place to work for 16 years in a row. We offer competitive compensation packages, comprehensive healthcare benefits, and other perks and incentives to ensure our employees feel valued and supported.

Thanks to our commitment to creating a supportive and engaged workplace culture, Gorilla Glue has been recognized as a top place to work for 16 years in a row. We offer competitive compensation packages, comprehensive healthcare benefits, and other perks and incentives to ensure our employees feel valued and supported. Joining the Gorilla Glue family means being part of a team passionate about building strong brands and promoting a culture of excellence.

As an employee, you'll be able to help create high-quality products and build brands that people love. Join us in an inspiring workplace where you can belong, grow, and make a difference!

The Manager, Data Products & Governance leads the enterprise data product portfolio, the master data management program, and the data governance program that supports how data and artificial intelligence are used across the company. The role has three pillars, described below: data product management, master data management, and data governance and AI enablement. It also leads a team of three data governance and master data specialists, with responsibility for their priorities, development, and day-to-day execution.

Together these pillars set the standards, ownership model, and controls that make data trusted, well understood, and appropriately protected; keep master data accurate and consistent across the systems that depend on it; support the practical guardrails that let teams adopt AI capabilities safely and productively rather than informally and invisibly; and prioritize the data product work that turns standards into capabilities people actually use.

Beyond the team, the role leads through influence: holding governance forums, developing a federated network of data owners and stewards, and partnering across Information Technology, IT Security, Legal, Human Resources, Marketing, Supply Chain, and Finance to turn written policy into everyday practice. The division of responsibility between this role and the AI Center of Excellence is still being defined; this role brings the data expertise, standards, and controls that AI governance depends on, and partners with the COE on tool, model, and usage policy.

Decisions to purchase third-party or syndicated data sets rest with the business functions that hold the business case and the budget. This role defines the standards those data sets must meet, evaluates fit and quality, and advises on selection; it does not decide what is bought.

• Develop and maintain a prioritized roadmap for enterprise data products, aligned to business strategy and measurable value.
• Partner with business leaders and end users to understand the decisions, workflows, pain points, and opportunities that data products should support.
• Translate business needs into product requirements, user stories, acceptance criteria, and clear outcomes for data engineering, architecture, analytics, and application teams.
• Manage backlog prioritization and make tradeoff recommendations based on business impact, user value, risk, effort, dependencies, and data readiness.
• Guide data products through discovery, design, delivery, launch, adoption, enhancement, and retirement, including user validation and release readiness.
• Drive adoption through stakeholder communication, change planning, documentation, training coordination, and feedback loops.
• Identify opportunities to simplify fragmented reporting and data solutions, increase reuse, and reduce one-off or duplicative work.
• Partner with architecture and engineering to embed governance and product requirements into platform design, integration patterns, and semantic models rather than inspecting for them afterward.

• Lead the master data management program across domains such as item, customer, and supplier, setting standards for record creation, enrichment, validation, and change so master data stays accurate and consistent across the ERP and the systems that consume it.
• Govern master data intake and change workflows, including validation, approval routing, and turnaround…