Senior Microsoft Fabric Data Engineer
Senior Data Engineer acting as the Microsoft Fabric subject-matter expert at a credit union, designing enterprise-scale data platforms on OneLake, Lakehouse, and Data Warehouse, building ELT/ETL pipelines with Azure Data Factory, SQL, dbt, and PySpark, and guiding Fabric adoption across architecture and analytics teams.
- Compensation
- Not disclosed
- Location
- Vancouver, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- 8+ years of Data Engineering experience
- 2+ years delivering enterprise Microsoft Fabric solutions
- Expertise with OneLake, Lakehouse, Spark, PySpark, and SQL
- Strong enterprise ELT and ETL design experience
- Experience with Azure DevOps, Git, governance, and lineage
Full description
Microsoft Fabric expertise leads enterprise data engineering at Central 1, combining OneLake, Lakehouse, Data Warehouse, and scalable pipeline development.
As a Senior Data Engineer and Microsoft Fabric Subject Matter Expert, you will design, implement, and optimize enterprise-scale data platforms. The work includes Azure Data Factory, SQL, dbt, PySpark, Spark Notebooks, and Fabric Data Pipelines. You will also guide Fabric adoption across architecture and analytics stakeholders.
Key Responsibilities:
Design scalable pipelines across OneLake, Lakehouse, and Data Warehouse
Provide technical leadership and mentorship on Microsoft Fabric engineering
Develop and optimize ELT and ETL pipelines
Implement Bronze, Silver, and Gold Medallion Architecture
Optimize Fabric capacity utilization, performance, and governance
Requirements:
Eight or more years of Data Engineering experience
Two or more years delivering enterprise Microsoft Fabric solutions
Expertise with OneLake, Lakehouse, Spark, PySpark, and SQL
Strong enterprise ELT and ETL design experience
Experience with Azure DevOps, Git, governance, and lineage
Lead Microsoft Fabric engineering at Central 1 through scalable architecture, optimized pipelines, governance, and enterprise data platforms.