Data Quality Engineer

Trilon is building a supercharged, technology-enabled future for our people and partners. The Data Quality Engineer plays a critical role in that mission by ensuring the data that powers every AI and digital tool is accurate, consistent, complete, and trustworthy. 

This role owns data quality across the entire Data Platform, defining what good data looks like and ensuring that standard is enforced in practice. You are responsible for building the validation, monitoring, and observability systems that detect issues early and prevent bad data from reaching downstream tools where it erodes trust and usability. 

You maintain and evolve the enterprise data quality rubric, treating it as a living standard that governs how data is measured and evaluated across all pipelines and domains. You score data quality on a regular cadence and provide clear visibility into platform health, giving leadership an accurate view of where data is strong and where it needs improvement. 

You work closely with Data Engineers to embed quality checks into every pipeline, and with product and AI teams to understand how data quality issues surface in real tools. When issues arise, you trace them back to the source and resolve them at the pipeline level. 

This role requires strong data engineering fundamentals, experience building data quality frameworks, and a systematic approach to defining and enforcing standards. You are detail-oriented, structured in your thinking, and motivated by building a data foundation that engineers trust.