Senior Data Engineer

UL Standards & Engagement; Evanston (IL); Hybrid; USD 89,602 - 123,202; Full time

Benefits offered by this job

Comprehensive medical, dental, and vision insurance

401k matching up to 5%

Flexible working arrangements available

Job summary

UL Standards & Engagement is seeking a Senior Data Engineer for hybrid work based in Evanston, IL. The role involves designing and developing scalable data infrastructure to facilitate analytics and machine learning initiatives.

The ideal candidate will have at least 5 years of experience and a Bachelor’s degree in a related field. Responsibilities include managing complex datasets, developing ETL processes, and collaborating with diverse teams to create data solutions that meet the organization’s goals.

Qualifications

• Minimum 5 years of related work experience in data engineering.
• Experience designing and supporting enterprise-scale data platforms.
• Advanced proficiency in Python and SQL for data manipulation.

Responsibilities

• Design, build, and maintain scalable data architectures and platforms.
• Lead integration of complex datasets from diverse sources.
• Develop and optimize ETL/ELT processes for data accuracy.

Skills

Data architecture

Data integration

Data governance

Python

SQL

Project management

Communication

Education

Bachelor’s degree in Computer Science or related field

Tools

Azure Cosmos DB

SQL Server

Elasticsearch

Neo4j

Job description

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.

Key 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 & Experience

• People: Our people make us special. You’ll work with a diverse team of experts respected for their independence and transparency and build a network, because our approach is collaborative. We collaborate across disciplines, organizations, and geographies to build the global scientific response that today’s global challenges require.
• Interesting work: Every day is different for us here. We see what’s on the horizon and use our expertise to build the foundations of a safer future. You’ll have the opportunity to push the boundaries of human understanding as part of a team working to advance the public good.
• Grow and achieve: We learn, work, and grow together through targeted development, reward, and recognition programs.
• Values: Four core values guide our work: collaboration, respect, integrity, and beneficence. By living our values, we inspire the trust essential to fulfilling our mission and foster partnerships that enable us to pursue a beneficent future in which we all can thrive.
• Total Rewards: All employees at UL Standards & Engagement are eligible for bonus compensation. We offer comprehensive medical, dental, vision, and life insurance plans and a generous 401k matching structure of up to 5% of eligible pay. Moreover, we invest an additional 4% into your retirement saving fund after your first year of continuous employment. Depending on your role, you may be able to discuss flexible working arrangements with your manager. We also provide employees with paid time off, including vacation, holiday, sick, and volunteer days.

Professional Competencies

• 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.
• Demonstrated expertise in designing scalable solutions that support advanced analytics, machine learning, large language models, and Retrieval-Augmented Generation applications.
• Proficiency in 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 communication and engagement skills, with ability to convey complex information to various stakeholder group, 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 with ability to innovate and adapt in a dynamic industry landscape.

Professional Education and Experience Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering or related field. Advanced degree preferred.
• 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.
• Working knowledge of structured standards content formats (e.g., XML, STS/NISO) or legal/regulatory document corpora is preferred.

Salary Range

$89,602.01 - $123,202.76

Pay Type

Salary