Data Quality Engineer

Trilon is building a technology-enabled future and is seeking a Data Quality Engineer to ensure the accuracy, consistency, and trustworthiness of data across their Data Platform. This role involves defining data quality standards, implementing validation and monitoring systems, and collaborating with Data Engineers to resolve data quality issues.

Responsibilities:

• Define, maintain, and evolve the enterprise data quality rubric across all data domains
• Establish standards for data accuracy, completeness, consistency, timeliness, and reliability
• Ensure data quality expectations are clearly defined and consistently applied across the platform
• Govern how data quality is measured, scored, and reported
• Design and implement automated data quality checks within data pipelines
• Build validation rules that detect anomalies, schema drift, missing data, and inconsistencies
• Ensure issues are identified at the source before propagating downstream
• Continuously improve validation coverage and effectiveness
• Build and maintain observability systems for pipeline health, data freshness, and performance
• Monitor data flows for failures, delays, and unexpected changes
• Provide visibility into pipeline status and data quality metrics across the platform
• Implement alerting and reporting mechanisms for critical issues
• Diagnose data quality issues and trace them back to source systems or pipeline logic
• Partner with Data Engineers to resolve issues at the pipeline level
• Work with product and AI teams to understand how data issues impact tool behavior
• Ensure root causes are addressed and not repeated
• Work with the Lead Data Engineer to align on pipeline architecture and quality standards
• Partner with pod Data Engineers to embed quality checks into all pipelines
• Collaborate with Lead Engineers and Applied AI Engineers to understand downstream impacts
• Communicate data quality insights clearly to both technical teams and leadership
• Score and report on data quality across the platform on a defined cadence
• Provide leadership with a clear view of data health, risks, and improvement areas
• Identify systemic issues and drive improvements in data processes and standards
• Continuously refine data quality practices as the platform evolves

Requirements:

• Experience designing scalable technical architectures for AI or machine learning solutions in enterprise environments
• Strong understanding of large language models, vector databases, embeddings, prompt orchestration, and model serving
• Hands-on experience with Azure services including Azure OpenAI, Azure Machine Learning, and Azure Functions
• Familiarity with LLM frameworks and orchestration tools such as LangChain, Semantic Kernel, or custom agent frameworks
• Knowledge of enterprise security, responsible AI principles, and compliance frameworks such as GDPR and CCPA
• Proven ability to create architecture documentation and communicate effectively with technical and non-technical audiences
• Experience integrating AI solutions into platforms such as Power Platform, SharePoint, and Microsoft Teams
• Bachelor's or master's degree in computer science, data science, engineering, or related field
• Certifications in cloud architecture or AI/ML disciplines preferred