Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Company Overview