Sr. Fabric Data Engineer

Role: Sr. Fabric Data Engineer
Engagement Type: Contract-to-Hire (C2H - 3 Months)
Work Location: Remote (EST time zone)
Start: Immediate / ASAP
We are seeking a highly skilled Senior Data Engineer with strong expertise in Microsoft Fabric to design, build, and optimize modern data pipelines and analytics platforms. This role will work across Fabric's unified ecosystem-including Data Factory, Lakehouse, Data Warehouse, OneLake, and Power BI -to deliver scalable, governed, and high-performance data solutions.
The ideal candidate will have hands-on experience migrating legacy Azure or on-prem data platforms to Fabric, implementing Medallion architecture, and collaborating closely with analytics and business stakeholders.
Key Responsibilities
Data Engineering & Architecture

• Design, develop, and maintain end-to-end data pipelines using Microsoft Fabric.
• Ingest, transform, and model data using Fabric Data Factory (Pipelines) and Dataflows Gen2 .
• Build and manage Lakehouses, Data Warehouses, and OneLake for scalable analytics.
• Implement Medallion architecture (Bronze / Silver / Gold layers).

Analytics & BI Enablement

• Partner with analytics and business teams to design Power BI semantic models .
• Support high-performance reporting through optimized datasets and models.
• Enable downstream analytics through clean, well-modeled data layers.

Governance, Performance & Optimization

• Implement data governance, security, lineage, and compliance best practices.
• Optimize Fabric workloads for performance and cost efficiency .
• Monitor and troubleshoot pipelines using Fabric monitoring tools.

Integration & Automation

• Integrate Fabric with other Microsoft services:
  • Azure Synapse
  • Azure Data Lake
  • Power Platform
• Automate data quality checks and validation using:
  • Fabric Notebooks (Python / Spark)
  • Data Activator
• Support migration from Azure Synapse, Databricks, or SQL Server to Fabric.

Required Skills & Experience

• Strong hands-on experience with Microsoft Fabric :
  • Data Factory (Fabric Pipelines)
  • Lakehouse
  • Data Warehouse
  • OneLake
  • Power BI
• Advanced proficiency in SQL, Python, and Spark
• Experience with ETL / ELT , data modeling, and performance tuning
• Solid understanding of Medallion architecture
• Experience with Azure Data Services (Data Lake, Synapse, ADF v2)
• Knowledge of data governance, lineage, and security
• Experience with Git and CI/CD for data pipelines
• Hands-on experience with Power BI datasets, semantic models, and DAX (preferred)

Preferred Qualifications

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Experience migrating Azure data ecosystems to Fabric
• Exposure to real-time analytics / event-driven data
• Experience preparing ML datasets using Fabric Notebooks

Recruiter Submission Template -
Full Name:
Highest Degree (Field, Institution & Completion Year):
Total Years of Data Engineering Experience:
Total Years of Experience with Microsoft Fabric (Required):
Hands-on experience with Microsoft Fabric components (Yes/No):

• Data Factory / Fabric Pipelines:
• Dataflows Gen2:
• Lakehouse:
• Data Warehouse:
• OneLake:

Experience designing end-to-end data pipelines in Microsoft Fabric:
Experience ingesting and transforming data from multiple sources:
Experience building and managing Lakehouses and Warehouses:
Understanding of Medallion Architecture (Bronze-Silver-Gold):
Experience with Power BI datasets and semantic models:
Experience with DAX (Yes/No):
Experience collaborating with business/analytics teams:
Experience with Azure Data Services (Yes/No):

• Azure Data Lake:
• Azure Synapse:
• Azure Data Factory v2:

Experience integrating Fabric with other Microsoft services:
Experience implementing data governance, lineage, and security (Yes/No):
Experience automating data quality checks using Fabric Notebooks (Python/Spark) or Data Activator (Yes/No):
Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) (Yes/No):
Motivation for Interest in This Position:
Contact Number:
Email ID:
LinkedIn Profile URL:
Full Address (Street, City, State, Zip):
Notice Period (in weeks):
Current Work Authorization Status:
Expected Hourly Rate on W2:
Earliest Interview Availability:
Earliest Start Date: