Data Engineer
UL Solutions · Mexico
- Profile, analyze, and validate source data to understand structure, quality, business meaning, and transformation requirements.
- Design, develop, test, and maintain data pipelines that ingest, transform, and deliver data from internal and external sources.
- Build scalable ETL/ELT solutions across cloud data platforms, data warehouses, lakehouse patterns, and data integration tools.
- Develop and optimize SQL, stored procedures, scripts, and reusable data engineering components.
- Implement data quality checks, reconciliation controls, error handling, logging, lineage capture, and pipeline monitoring.
- Apply automated testing, version control, code review, continuous integration, and deployment practices.
- Monitor pipeline execution, investigate failures, resolve data issues, and support root cause analysis.
- Collaborate with business users, data owners, data stewards, architects, security teams, and platform engineers.
- Document technical designs, mappings, transformation logic, operational procedures, dependencies, and support information.
- Read and follow the Underwriters Laboratories Code of Conduct and all physical and digital security practices.
A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. UL Solutions delivers testing, inspection and certification services, together with software products and advisory offerings, that support our customers’ product innovation and business growth. The UL Mark serves as a recognized symbol of trust in our customers’ products and reflects an unwavering commitment to advancing our safety mission. We help our customers innovate, launch new products and services, navigate global markets and complex supply chains, and grow sustainably and responsibly into the future. Our science is your advantage.
The Data Engineer analyzes, designs, develops, tests, deploys, and maintains data pipelines and ETL/ELT solutions that acquire, transform, validate, and deliver data for reporting, analytics, automation, and data science use cases. This role partners with business stakeholders, data product owners, architects, senior engineers, and platform teams to assess source systems, evaluate solution options, resolve data and pipeline issues, support production operations, and deliver scalable, secure, and well-documented data engineering solutions.