Dnb
Industry Practice Expert, Utilities/Manufacturing/Commercial Industries (R-19613)
Florham Park - New Jersey - United States
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- Role family
- Sales
- Seniority
- Mid level
- Stated salary
- $140,400 – $235,900 per year
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 21 Sept 2026
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the posting
Shape the Future with Dun & Bradstreet
At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers .
As an Industry Practice Expert for Utilities and Manufacturing at Dun & Bradstreet, you will play a pivotal role in the sales cycle by building credibility and trust with utility providers, energy companies, manufacturers, industrial suppliers, automotive and transportation organizations, and related ecosystem partners around Dun & Bradstreet’s data and analytics solutions. Your primary responsibility is to align our products and services with industry-specific needs—such as supplier discovery and qualification, supply chain resilience, customer and supplier master data, credit and financial risk, compliance, ESG and climate exposure, account planning, and AI-ready data foundations—offering a tailored solution architecture that leverages our existing and future capabilities to solve critical business challenges.
In this role, you will collaborate closely with internal teams—across product, data and analytics, partnerships, advisory, marketing, sales, and customer success—to ensure Dun & Bradstreet’s solutions address the evolving challenges of Utilities and Manufacturing markets, including complex global supplier networks, operational disruption, regulatory and reporting requirements, capital-intensive business models, sustainability expectations, and the need for trusted data to support automation, analytics, and AI-enabled decisioning.
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