Position Overview
We’re partnering with a Vancouver-based client currently undergoing a large-scale enterprise data platform modernization, migrating their environment to Microsoft Fabric. This is a fully remote, 6-month contract with strong potential for extension, supporting a high-impact, fast-moving migration initiative.
This is a deadline-driven project with a planned go-live at the end of August. The team is in active build mode and requires hands-on Fabric engineers who can immediately contribute to pipeline development, data transformations, and stabilizing workloads.
The architecture and source mappings are already defined by the internal team. This role is focused on execution, build, and optimization, not design ownership.
What You’ll Be Doing
As a Microsoft Fabric Data Engineer, you will play a key role in building and scaling the organization’s modern data platform within Fabric.
You’ll be working in a high-volume, sprint-based environment, helping migrate and operationalize data pipelines across the medallion architecture (bronze → silver → gold).
Key Responsibilities
Build and maintain data ingestion pipelines using Microsoft Fabric Data Factory to ingest data into OneLake (bronze layer)
Develop and manage data transformations (bronze → silver → gold) using PySpark and Fabric notebooks, writing to Delta lakehouse environments
Implement and structure gold-layer data models optimized for reporting and analytics
Build and support semantic models (Direct Lake / Power BI)
Translate predefined source-to-target mappings into working pipelines and transformations
Troubleshoot and resolve pipeline failures, performance issues, and data inconsistencies
Optimize Spark workloads and pipeline performance
Work within a Git-based workflow (feature branches, pull requests) no direct production deployments
Collaborate with data architects and internal teams while working within a defined architecture
Required Skills & Experience
Proven, recent hands-on experience with Microsoft Fabric
Strong experience in data ingestion and pipeline development (Fabric Data Factory / Copy activities)
Proficiency in PySpark for large-scale data transformations
Experience working with Delta Lake / lakehouse architectures
Strong understanding of medallion architecture
Solid SQL and data modeling experience
Experience with semantic models and Power BI datasets
Ability to troubleshoot, debug, and optimize pipelines under tight timelines
Experience working in Agile, sprint-driven delivery environments
Ability to work independently and deliver with minimal ramp-up or oversight
Nice to Have
Microsoft Purview / data governance exposure
Experience in regulated environments (healthcare, financial services)
Familiarity with Azure services (Entra ID, Key Vault, networking, private endpoints
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