Senior Data Engineer

About the role

The Senior Data Engineer supports a diverse portfolio of standards and data science initiatives at UL Standards & Engagement (ULSE) to advance the mission of making the world safer, more secure, and sustainable.

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

Requirements

• 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 groups, including technical and non-technical audiences.
• Possession of a 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.

Qualifications

• 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.

Skills

• Data architecture
• Data integration
• Data modeling
• Data governance
• ETL/ELT processes
• AI and RAG data infrastructure
• Database technologies
• Cloud-based data platforms
• Project management
• Communication and engagement
• Independent judgement

Benefits

• Comprehensive medical, dental, vision, and life insurance plans
• Generous 401k matching structure of up to 5% of eligible pay
• Additional 4% contribution to your retirement saving fund after your first year of continuous employment
• Paid time off, including vacation, holiday, sick, and volunteer days

Pay

$89,602.01 - $123,202.76

Schedule

Hybrid opportunity based in our Raleigh-Durham, NC or Evanston, IL office.