Analytics Engineer

Loenbro is a trusted construction lifecycle partner serving various industries across the U.S. They are seeking an Analytics Engineer responsible for designing, building, and maintaining data pipelines and models to support reliable reporting within their data platform.

Responsibilities:

• Design, build, and maintain data pipelines that ingest and transform data from source systems into the Loenbro lakehouse on Microsoft Fabric
• Integrate data from ERP systems, project management platforms, APIs, and other operational sources into the lakehouse
• Enforce data quality standards — building validation logic, monitoring pipelines, and resolving data integrity issues before they surface in reports
• Use the medallion architecture — structuring bronze, silver, and gold layers to ensure data is clean, consistent, and ready for consumption by the BI team
• Build and maintain fact and dimension tables and semantic models that serve as the trusted, authoritative data layer for all reporting
• Collaborate with the team to understand reporting requirements and ensure the data model supports the metrics and KPIs the business needs
• Document data models, pipeline logic, and transformation rules so the team can understand, maintain, and extend the platform over time
• Manage deployments using SDLC and ALM best practices — version control, environment promotion, and change management
• Stay current on Microsoft Fabric capabilities and proactively recommend improvements to the data platform architecture

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field
• 3–5+ years of experience in data engineering, analytics engineering, or a closely related technical discipline
• Demonstrated experience building and maintaining data pipelines in a production environment
• Hands-on experience with medallion architecture (bronze/silver/gold layers) and lakehouse design
• Microsoft Fabric — required; Lakehouses, Data Warehouses, Dataflows Gen2, Data Pipelines, PySpark Notebooks, and OneLake
• SQL — required; complex queries, stored procedures, transformation logic, and performance tuning
• Python or another scripting language — required; pipeline automation, data transformation, and custom tooling
• ETL/ELT design patterns and data integration from multiple source systems
• OneLake, Delta Lake, and Parquet-based storage formats
• CI/CD practices and version control (Git/Azure DevOps) applied to data pipelines and deployments
• SDLC and ALM process discipline — moving solutions responsibly from development through production
• Strong command of fact and dimension table design — star schema, snowflake schema, and conformed dimensions
• Experience building and publishing semantic models / datasets that serve as the trusted layer the BI team builds reports against
• Data quality, lineage, and governance principles — understanding how to build trust in a data platform
• DAX proficiency for semantic layer logic, calculated measures, and KPI definitions
• Ability to optimize semantic models for performance, scalability, and reuse across multiple reports
• Power Platform experience (Power Automate, Power Apps)
• AI/ML exposure — integrating AI-assisted pipelines or LLM outputs into data workflows
• Software development background in any additional language
• Microsoft DP-700 (Fabric Data Engineer Associate) or DP-600 (Fabric Analytics Engineer) certification
• Construction or heavy industry experience is a plus