We have an exciting opportunity foraSenior Data EngineeratUL Standards & Engagement.This is a hybrid opportunity based inourRaleigh-Durham, NCor Evanston, ILoffice.

TheSenior Data Engineerwill 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 thatsupportanalytics, machine learning, and emerging AI capabilities. Leveragingexpertisein modern data architecture, cloud technologies, and advanced data engineering practices, the Senior Data Engineer will transform complexstandardscontent 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.

Whatyoulllearnandachieve:

AstheStandards Publications Specialist,youwill play a key role in the rapid growth ofULas you:

• Design, build, andmaintainscalable data architectures, platforms, and pipelines that supportstandardsdevelopment, 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 HTMLstandardscontent, relational databases, and unstructured information repositories.

• Develop andoptimizeenterprise 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, metadata frameworks, and data quality controls that support enterprise reporting, machine learning applications, and large language model initiatives.

• Design and deploy production-grade RAG infrastructure, including document ingestion, content chunking strategies, metadata enrichment, embedding generation, vector storage, and hybrid retrieval methodologies.

• Evaluate, implement, andoptimizedatabase technologies and retrieval systems to support high-performance search, semantic context retrieval, and AI-enabled knowledge discovery.

• Collaborate with business leaders, standards development subject matter experts, and technical teams to translate complex business challenges into scalable data solutions and infrastructure investments.

• Establishand promote best practices for data governance, security, privacy, and lifecycle management while ensuring compliance with applicable regulations, intellectual property protections, and organizational standards.

• Monitor, troubleshoot, and continuously improve data platform performance, reliability, scalability, and operational efficiency.

• Contribute to the development and execution of data strategy,identifyingopportunities to expand organizational capabilities through modern data engineering practices and emerging technologies.

• Mentor andprovidetechnical guidance to data engineers, analysts, and cross-functional team members, fostering adoption of scalable engineering standards and best practices.

• Prepare andmaintaintechnical documentation, architectural designs, andimplementationroadmaps that support knowledge sharing and long-term sustainability of data platforms.

• Make notable contributions to shared team goals and independently manage workload effectively, usingappropriate communicationand adherence to deliverable and timeline expectations.

• Maintaincontinued awareness of industry trends and external context related to the portfolio.

• Perform other duties as directed.

Whatmakes you a great fit:

While no one candidate will embody every quality, the successful candidate will bring many of the following professional competencies and personal attributes:

• Advanced application of data engineering principles, including data architecture, integration, modeling, governance, and large-scale pipeline development within complex technical environments.

• Strong technical aptitude in modern cloud-based data platforms, database technologies, distributed processing frameworks, and AI-enabled data infrastructure.

• Demonstratedexpertisein designing scalable solutions that support advanced analytics, machine learning, large language models, and Retrieval-Augmented Generation applications.

• Proficiencyin project management with experience developing project timelines, scope, and managing project resources. Ability to apply independent judgement in selecting methods, assessing results, and refining solutions.

• Strong communicationand engagement skills, withabilityto convey complex information to various stakeholdergroup, including technical and non-technical audiences.

• Positive and collaborative interpersonal skills, with proven capability in fostering collaboration and partnership across teams to develop solutions with broad impact.

• Commitment to continuous learning, technical excellence, and the adoption of emerging technologies that strengthen organizational capabilities and business outcomes.

• Strategic thinker withabilityto innovate and adaptina dynamic industry landscape.

Professional education and experience requirements for the role include:

• Bachelors degree in Computer Science, Data Engineering, In