Hybrid Data Engineer: Cloud ETL/ELT & Data Quality

UL Solutions; Mexico; Hybrid; MXN 600,000 - 900,000; Full time

Job summary

UL Solutions is seeking a Data Engineer to profile, validate, and transform source data while building scalable ETL/ELT pipelines across cloud platforms and data warehouses. You’ll optimize SQL, implement data quality checks, and collaborate with data owners, architects, and security teams to ensure robust data products.

Responsibilities include monitoring pipelines, CI/CD, and documentation, with emphasis on secure data handling and governance. Hybrid work model in a global team.

Qualifications

• Bachelor’s degree in computer science, information systems, engineering, data analytics, mathematics, or related discipline or equivalent experience.
• Experience designing, developing, testing, and supporting data pipelines, ETL/ELT processes, integrations, or analytic data solutions.
• Strong SQL skills, including query development, troubleshooting, transformation logic, and performance tuning.
• Experience with cloud data platforms and data warehouses or lakehouse technologies such as Snowflake, Azure data services, SQL Server.
• Understanding of data profiling, data quality, validation, structured, semi-structured, and unstructured data concepts.
• Familiarity with dimensional modeling, curated datasets, semantic layers, and analytics-ready data products.
• Experience with Git-based version control, code review, automated testing, CI/CD, and agile delivery practices.
• Ability to isolate root causes, communicate clearly, and apply secure data handling, governance, lineage, privacy, and access control concepts.

Responsibilities

• 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.

Skills

SQL

ETL/ELT

Data pipelines

CI/CD

Git version control

Data quality

Data governance

Communication

Problem solving

Education

Bachelor’s degree in Computer Science / Information Systems / Engineering / Data Analytics

Tools

Snowflake

Azure data services

SQL Server

Job description

UL Solutions is seeking a Data Engineer to profile, validate, and transform source data while building scalable ETL/ELT pipelines across cloud platforms and data warehouses. You’ll optimize SQL, implement data quality checks, and collaborate with data owners, architects, and security teams to ensure robust data products.

Responsibilities include monitoring pipelines, CI/CD, and documentation, with emphasis on secure data handling and governance. Hybrid work model in a global team.