Job Description
Why We Work at Dun & Bradstreet
Dun & Bradstreet combines global data and local expertise to help clients make smarter decisions. With 6,000+ people in 31 countries, we are a team of diverse thinkers and problem solvers who all share a common curiosity: to find new ways to turn data into value. If you share this curiosity and want to be part of a future-ready company, come join us! Learn more at dnb.com/careers.
We are seeking a highly skilled Senior AI Data Engineer to architect and build scalable data pipelines and infrastructure for AI and Generative AI applications. This role focuses on managing unstructured data, embedding generation, and vector database operations to support advanced AI workflows such as Retrieval-Augmented Generation (RAG), semantic search, and agentic systems.
You will work closely with AI engineers, data scientists, and platform architects to deliver high-performance, secure, and resilient data systems that power enterprise-grade AI solutions.
About you:
- Bachelor’s or master’s degree in computer science, Data Engineering, or related field.
- 8+ years of experience in data engineering, with at least 3 years managing unstructured data and embedding pipelines
- Strong proficiency in Python, and data pipeline tools (Dataflow, Pub/Sub, Cloud Functions, Cloud Storage, Apache beam, Air Flow, Vertex AI Pipelines, Kafka, Flink).
- Experience with embedding models and vector search platforms (e.g., BigQuery Vector Search, QDRANT)
- Deep understanding of unstructured data processing, especially text, PDFs, etc.
- Familiarity with cloud platforms (Azure, GCP, AWS) and services like Databricks, Vertex AI, and Dataflow.
- Knowledge of containerization and microservices (Docker, Kubernetes).
- Experience with CI/CD pipelines, Terraform, and DevSecOps practices.
- Hands-on experience with hybrid search and agentic workflows.
- Familiarity with multimodal analytics and joining structured/unstructured data for advanced use cases.
- Contributions to platform-level services such as RAG-as-a-Service and embedding generation frameworks.
Desirable Experience
We appreciate you may not meet all listed criteria above, but if you have the passion and eagerness to learn and grow, we want to hear from you!!
All employees and contractors working in D&B should be aware that they have responsibilities in relation to the Company’s Business Management System. This relates to information and its security, quality, environment and health and safety both during and post-employment with D&B.
Dun & Bradstreet is an Equal Opportunity Employer
All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.
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Requirements
About you:
- Bachelor’s or master’s degree in computer science, Data Engineering, or related field.
- 8+ years of experience in data engineering, with at least 3 years managing unstructured data and embedding pipelines
- Strong proficiency in Python, and data pipeline tools (Dataflow, Pub/Sub, Cloud Functions, Cloud Storage, Apache beam, Air Flow, Vertex AI Pipelines, Kafka, Flink).
- Experience with embedding models and vector search platforms (e.g., BigQuery Vector Search, QDRANT)
- Deep understanding of unstructured data processing, especially text, PDFs, etc.
- Familiarity with cloud platforms (Azure, GCP, AWS) and services like Databricks, Vertex AI, and Dataflow.
- Knowledge of containerization and microservices (Docker, Kubernetes).
- Experience with CI/CD pipelines, Terraform, and DevSecOps practices.
- Hands-on experience with hybrid search and agentic workflows.
- Familiarity with multimodal analytics and joining structured/unstructured data for advanced use cases.
- Contributions to platform-level services such as RAG-as-a-Service and embedding generation frameworks.
Desirable Experience
We appreciate you may not meet all listed criteria above, but if you have the passion and eagerness to learn and grow, we want to hear from you!!
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