Data Engineer

• Own and lead the technical strategy and architecture for the DI&T analytics data platform and semantic layer
• Design and develop scalable data models and curated datasets
• Define and lead the analytics semantic layer, including business logic, metrics, dimensions, relationships, and definitions
• Lead reliable production data pipelines and transformation processes
• Integrate data from operational systems, warehouses, integration hubs, data lakes, and enterprise sources
• Translate business and analytical requirements into scalable, reusable data solutions
• Solve complex cross-system data problems and develop innovative solutions
• Establish and apply data modeling, engineering, and governance standards
• Implement validation, testing, monitoring, and error handling to ensure data quality and reliability
• Provide technical leadership and mentorship to analysts, engineers, and technical team members
• Serve as subject matter expert for data modeling, dbt, Snowflake, SQL, and analytics engineering
• Monitor pipeline and model performance and implement sustainable improvements
• Partner with technology and engineering teams to evolve data architecture
• Identify opportunities to centralize data, automate workflows, improve integration, and strengthen the data foundation
• Set technical priorities aligned with business objectives
• Communicate technical concepts, risks, trade-offs, and recommendations to technical and non-technical audiences

Explore Principal Data Engineer at IDEXX. Review requirements and application details.