Data Engineer

Trilon is building a supercharged, technology-enabled future for their people and partners. The Data Engineer plays a key role in that mission by building and maintaining the data platform that powers Trilon’s enterprise analytics, automation, and AI capabilities.

Responsibilities:

• Serve as the primary owner and technical steward of the Trilon enterprise data platform
• Design, develop, and maintain data pipelines and workflows using Azure Data Factory, Synapse, and Microsoft Fabric
• Build and manage data transformations, orchestration, and automation across structured, semi-structured, and unstructured data sources
• Ensure scalability, reliability, and performance of the data platform as Trilon continues to grow through acquisition
• Implement monitoring and alerting to proactively detect and resolve pipeline or data quality issues
• Develop and maintain integrations between Trilon’s enterprise systems, cloud services, and acquired partner environments
• Design and maintain a unified, scalable data model that harmonizes data across business systems
• Build secure, governed, and high-performance Power BI semantic models optimized for analytics and self-service reporting
• Collaborate with business analysts and data consumers to ensure data models support enterprise reporting needs and KPIs
• Partner with cybersecurity and infrastructure teams to ensure data models and access patterns meet compliance and governance standards
• Implement validation and quality checks to ensure accuracy, completeness, and timeliness of enterprise data sets
• Maintain metadata, lineage, and documentation to promote transparency and reusability
• Define and enforce data quality and consistency standards across all integrated sources
• Collaborate with the Technology Asset Manager and Service Platform Manager to align system integrations and data governance
• Support data cataloging, discovery, and classification initiatives within Microsoft Purview or equivalent tools
• Develop automated frameworks for ingestion, transformation, and validation using Azure-native tools and pipelines
• Implement DevOps principles for data workflows including version control, testing, and deployment automation
• Optimize pipeline performance, resource utilization, and data freshness
• Build resilience and fault tolerance into data operations to ensure reliability and recovery
• Create reusable components and templates to streamline integration of new data sources and partner systems
• Collaborate with the AI and Innovation vTeam to prepare and structure data for AI, ML, and RAG-based applications
• Develop and maintain data pipelines that support model training, evaluation, and fine-tuning
• Curate and transform unstructured data for retrieval, embedding, and vectorization within AI applications
• Ensure data readiness for generative AI tools, chat interfaces, and knowledge retrieval systems
• Stay informed of emerging AI data engineering trends and Microsoft Fabric AI integrations
• Partner with application and infrastructure teams to ensure reliable and secure data exchange across systems
• Collaborate with business stakeholders and analysts to understand reporting needs and deliver usable data models
• Support integration engineers in onboarding new firms and ensuring their data aligns with Trilon’s enterprise model
• Work closely with cybersecurity and compliance teams to enforce data protection, retention, and access policies
• Provide documentation, architecture diagrams, and operational standards for the data platform and pipelines

Requirements:

• 5 or more years of experience in data engineering, data integration, or data platform development
• Strong hands-on experience with Azure Data Factory, Azure Synapse, Microsoft Fabric, and related Azure data services
• Proficiency in SQL, DAX, Power Query, and data modeling for Power BI
• Experience designing and maintaining Power BI semantic models, datasets, and row-level security configurations
• Familiarity with data governance, cataloging, and lineage management in tools like Microsoft Purview
• Experience building and optimizing cloud data pipelines with structured, semi-structured, and unstructured data
• Understanding of data preparation for AI and machine learning applications, including RAG architectures
• Exposure to engineering and geospatial data such as CAD, BIM, and GIS
• Strong analytical and problem-solving skills with a focus on scalability and performance
• Excellent collaboration and communication skills across technical and business audiences
• Bachelor's degree in Computer Science, Data Engineering, or related field preferred
• Microsoft certifications such as Azure Data Engineer Associate or Fabric Analytics Engineer Associate are a plus