Responsibilities
- Design and implement a Microsoft Fabric lakehouse + warehouse architecture on OneLake, with Bronze and Silver layers in the Lakehouse and curated Gold data products in the Warehouse.
- Build and maintain ingestion, transformation, and publishing pipelines using Fabric and related Azure services, including Data Factory pipelines, Lakehouse, Warehouse, notebooks/Spark, and SQL.
- Integrate data from key AEC systems—including project delivery, documents, financials, scheduling, and GIS/BIM-related sources—and develop repeatable onboarding patterns using incremental loads, CDC where appropriate, monitoring, alerting, and runbooks.
- Publish trusted data products, metadata, and lineage that support AI use cases such as enterprise search, copilots, and retrieval-based applications.
- Partner with IT and security to establish data quality, governance, access controls, data classification, lifecycle policies, and production DataOps practices.
Requirements
- 5+ years of experience in data engineering, analytics engineering, or building production-grade data platforms and pipelines.
- Strong SQL skills and experience with relational and analytical data modeling, transformation design, and curated datasets for downstream use.
- Proficiency in Python and/or Spark, plus experience with orchestration tools such as Microsoft Fabric Data Factory pipelines or Azure Data Factory.
- Experience supporting production data workloads, including incremental loading or CDC patterns, monitoring, CI/CD, governance, and collaboration across technical and business teams.
Nice to Have
- Hands-on experience with Microsoft Fabric strongly preferred; equivalent experience with Azure-based lakehouse, warehouse, or modern data platform services will also be considered.
- Experience implementing medallion architecture patterns in Microsoft Fabric.
- Experience preparing enterprise data for AI or LLM-driven use cases, including metadata enrichment, chunking, embeddings workflows, or retrieval optimization.
- Familiarity with Azure AI Search, vector or hybrid retrieval patterns, and secure enterprise search architectures.
- Familiarity with data catalog, governance, and lineage tools such as Microsoft Purview or similar platforms.
- AEC domain familiarity, including project delivery data, GIS, BIM/CAD metadata, and document workflows.
Work Arrangement
On-site — St. Paul, Minnesota (MN)
Additional Information
- Partner with IT, security, and civil engineering leadership
- Role involves building a Microsoft Fabric–based lakehouse + warehouse platform on OneLake
- Design and implement data architecture with Bronze, Silver, and Gold layers
- Build and maintain ingestion, transformation, and publishing pipelines
- Integrate data from AEC systems including project delivery, documents, financials, scheduling, and GIS/BIM-related sources
- Publish trusted data products for AI use cases such as enterprise search, copilots, and retrieval-based applications
- Establish data quality, governance, access controls, data classification, lifecycle policies, and production DataOps practices
