Big Data Graph Engineer (R-18356)

Why work at Dun & Bradstreet

Dun & Bradstreet analyzes the power of data to create a better future. Every day, we explore new ways to continuously promote a culture of excellence, accelerate innovation and growth. Over 6,000 employees worldwide are passionate about their work. We are committed to helping clients turn the unknown into confidence, risk into opportunity, and potential into growth. We always welcome diverse talents who dare to dream. Come join us!

Responsibilities

• Responsible for building and optimizing enterprise-level knowledge graph systems, designing graph architecture and data models;
• Participate in large-scale heterogeneous data collection, cleaning, fusion, and graph construction, improving data quality and graph coverage;
• Design and implement graph database query optimization, graph computing algorithms and graph service interfaces;
• Work closely with product, data science, and business teams to promote the application of graph technology in recommendation, search, risk control, intelligent Q&A and other scenarios;
• Track graph technology development trends and continuously promote technological innovation and platform capability upgrades.

Requirements

• Master's degree or above in Computer Science, Software Engineering, Artificial Intelligence, or related fields, with solid programming skills (Java/Python/Scala);
• 3+ years of experience in big data or knowledge graph, familiar with graph databases (e.g., Neo4j, JanusGraph, Nebula) and their applications;
• Familiar with mainstream big data technology stacks, such as Hadoop, Spark, Flink, Kafka, ElasticSearch, etc.;
• Familiar with core technologies such as graph computing, graph embedding, entity relationship extraction, knowledge fusion;
• Possess good system design ability, problem analysis ability, and teamwork ability;
• Good English reading and writing skills, proficient in written communication.

Plus Points

• Contributors to open-source projects preferred;
• Familiar with application scenarios combining LLM and knowledge graphs preferred;
• Experience in implementing large-scale knowledge graph projects preferred, with AI/NLP background preferred.

Application Guide

If you wish to apply for this position, please click the "Apply for this job" button. The screen will jump to a new page displaying the following fields: Resume, Full Name, Email, Phone Number, and Current Company. You can choose to provide links to your LinkedIn, GitHub, portfolio, Twitter, or other websites. You can also add recommendation letters, more personal information, or your interest in this position in "Additional Information". Finally, please click the "Submit Application" button to complete your application. We look forward to your application!