Senior Data Engineer

We have an exciting opportunity for a Senior Data Engineer at UL Standards & Engagement. This is a hybrid opportunity based in our Raleigh-Durham, NC or Evanston, IL office. 

The Senior Data Engineer will support a diverse portfolio of standards and data science initiatives to advance the mission of UL Standards & Engagement (ULSE) to make the world safer, more secure, and sustainable. The Senior Data Engineer will design, develop, and scale enterprise data infrastructure that support analytics, machine learning, and emerging AI capabilities. Leveraging expertise in modern data architecture, cloud technologies, and advanced data engineering practices, the Senior Data Engineer will transform complex standards content and enterprise data into reliable, accessible, and scalable assets. The Senior Data Engineer will serve as a critical bridge between foundational data systems and advanced analytical applications, partnering closely with technical leaders, standards development engineers, and data scientists to shape enterprise data strategy, build infrastructure supporting Generative AI and Retrieval-Augmented Generation (RAG) solutions, and enable informed decision-making across the organization. 

UL Standards & Engagement: 

At UL Standards & Engagement (ULSE), we expand the boundaries of safety science to create a more secure and sustainable world. For more than a century, we have created new safety standards and shared our findings with academia, scientists, manufacturers, and policymakers across industries. We identify critical safety and sustainability issues, asking tough questions because we believe a safer world begins with knowledge. 

Build a safer, more secure, and sustainable future with us. Join us and work with our Standards teams who develop the standards required to put that knowledge into practice. 

What you’ll learn and achieve: 

As the Standards Publications Specialist, you will play a key role in the rapid growth of UL as you: 

• Design, build, and maintain scalable data architectures, platforms, and pipelines that support standards development, research, analytics, reporting, and AI-driven initiatives across the organization. 

• Lead the collection, integration, and management of complex datasets from diverse sources, including APIs, structured XML and HTML standards content, relational databases, and unstructured information repositories. 

• Develop and optimize enterprise ETL/ELT processes to ensure the accuracy, consistency, availability, and performance of data assets used across analytical and operational environments. 

• Architect and implement robust data models, meta