Senior Data Engineer

UL Standards & Engagement • Evanston, IL

10d • $89,602 - $123,203 • Hybrid

About The Position

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.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering or related field.
• Minimum 5 years of related work experience.
• Progressively responsible experience designing, developing, and supporting enterprise-scale data platforms, architectures, and pipelines.
• Experience manipulating large datasets, utilizing databases for advanced data management, and integrating third-party data sources.
• Advanced proficiency in Python and SQL, with experience leveraging scripting, automation, and infrastructure configuration tools such as YAML, Bash, or PowerShell.
• Experience working with relational and non-relational database technologies, including platforms such as SQL Server, Elasticsearch, Neo4j, Azure Cosmos DB, MongoDB, or comparable solutions.
• Experience designing and implementing AI and RAG data infrastructure, including document processing, embedding generation, vector databases, and retrieval optimization techniques.

Nice To Haves

• Advanced degree preferred.
• Working knowledge of structured standards content formats (e.g., XML, STS/NISO) or legal/regulatory document corpora is preferred.

Responsibilities

• 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, 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, and optimize database 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.
• Establish and 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, identifying opportunities to expand organizational capabilities through modern data engineering practices and emerging technologies.
• Mentor and provide technical guidance to data engineers, analysts, and cross-functional team members, fostering adoption of scalable engineering standards and best practices.
• Prepare and maintain technical documentation, architectural designs, and implementation roadmaps that support knowledge sharing and long-term sustainability of data platforms.
• Make notable contributions to shared team goals and independently manage workload effectively, using appropriate communication and adherence to deliverable and timeline expectations.
• Maintain continued awareness of industry trends and external context related to the portfolio.
• Perform other duties as directed.

Benefits

• bonus compensation
• comprehensive medical, dental, vision, and life insurance plans
• generous 401k matching structure of up to 5% of eligible pay
• an additional 4% into your retirement saving fund after your first year of continuous employment
• flexible working arrangements
• paid time off, including vacation, holiday, sick, and volunteer days

What This Job Offers

• Job Type: Full-time
• Career Level: Senior