Dun & Bradstreet operates a graph-native data platform (Neo4j, JanusGraph, Nebula) feeding business intelligence and risk decisioning solutions across finance, credit, supply chain, and compliance. Active hiring skews heavily toward sales (22 roles) and data teams (17), with significant engineering effort on AI agents and Microsoft Fabric pipelines—revealing a shift toward real-time decisioning and copilot-driven workflows. Internal pain points around data governance for AI, copilot capacity monitoring, and cross-sell execution suggest they're scaling an intelligence platform while managing complexity of distributed agentic systems.
Notable leadership hires: Data Operations Lead
Dun & Bradstreet is a public information services company headquartered in Jacksonville, Florida, with 5,001–10,000 employees operating across nine countries including the US, India, China, and Western Europe. The company provides business decisioning data, credit and risk analytics, and compliance solutions to enterprises spanning finance, marketing, sales, and supply chain management. Its platform integrates graph databases, Apache streaming infrastructure (Kafka, Spark, Flink), and cloud data systems (Fabric, Elasticsearch) to deliver third-party risk assessments, revenue-acceleration insights, and operational intelligence. Recent project work centers on agentic AI workflows, Fabric-based data pipelines, and Salesforce maintenance, indicating modernization of core decisioning infrastructure.
Neo4j, JanusGraph, Nebula (graph databases); Kafka, Apache Spark, Apache Flink (streaming); Hadoop, Elasticsearch (big data); Workday (ERP); Salesforce (CRM); Marketo (marketing automation); Kubernetes, Docker (containerization); LangChain, LangGraph, LangSmith, RAG (LLM frameworks).
Scalable data pipelines in Microsoft Fabric; copilot agent development and integration; agentic workflow orchestration; data supply chain transformation; Salesforce data maintenance; Workday financial reporting; enterprise system integration; governance and compliance automation for AI workloads.
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