Senior Data Engineer

ULSE; North Carolina; Hybrid; USD 89,602 - 123,202; Full time

Benefits offered by this job

Bonus compensation

Comprehensive medical, dental, vision, and life insurance

401(k) matching

Flexible working arrangements

Paid time off

Job summary

ULSE is seeking a Senior Data Engineer for a hybrid role in Raleigh-Durham, NC, to design, build, and maintain scalable data architectures. Candidates should have a strong background in data engineering principles, with at least 5 years of relevant experience.

Responsibilities include optimizing ETL processes and collaborating with teams to translate business challenges into data solutions. Competitive benefits and a salary range of $89,602.01 – $123,202.76 enhance this opportunity.

Qualifications

• Minimum 5 years of related work experience.
• Proficiency in Python and SQL.
• Advanced application of data engineering principles.

Responsibilities

• Design and maintain scalable data architectures and platforms.
• Collaborate with technical teams to develop data solutions.
• Monitor and improve data platform performance.

Skills

Data architecture

Data integration

Python

SQL

Project management

Data modeling

Data governance

AI technologies

Collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

SQL Server

Elasticsearch

Azure Cosmos DB

MongoDB

Job description

SENIOR DATA ENGINEER

We have an exciting hybrid opportunity based in Raleigh‑Durham, NC or Evanston, IL, to support a diverse portfolio of standards and data science initiatives and advance UL Standards & Engagement’s mission to make 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.
• 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.

Qualifications

• 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.
• 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.
• 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; 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.

Benefits

• All employees are eligible for bonus compensation.
• Comprehensive medical, dental, vision, and life insurance.
• Generous 401(k) matching up to 5% of eligible pay, plus an additional 4% after the first year of continuous employment.
• Flexible working arrangements may be discussed with the manager.
• Paid time off, including vacation, holiday, sick, and volunteer days.

Salary Range: $89,602.01 – $123,202.76