Job Summary
We are seeking an experienced and highly skilled Data Architect with strong expertise in Microsoft Fabric, Azure Data Platform, Databricks, and Apache Spark to lead the design and implementation of enterprise-scale data modernization initiatives.
The ideal candidate will have extensive experience architecting cloud-native data platforms, defining data strategies, and delivering scalable, secure, and high-performing data solutions across complex business environments.
This role requires deep technical knowledge of Microsoft Azure data services, up-to-date data architecture patterns, data governance frameworks, and large-scale analytics platforms. Experience within the Insurance domain is highly desirable.
Responsibilities
Key Responsibilities
Data Architecture & Strategy
Define and drive enterprise data architecture strategies aligned with business objectives and technology roadmaps.
Design scalable, secure, and high-performance data platforms leveraging Microsoft Fabric, Azure, and Databricks ecosystems.
Establish architecture standards, best practices, reusable design patterns,



and governance frameworks for enterprise data solutions.
Lead cloud data modernization and migration initiatives from legacy platforms to cloud-native architectures.
Create architecture blueprints, reference architectures, and implementation roadmaps.
Microsoft Fabric Leadership
Architect and implement end-to-end solutions using:
Microsoft Fabric Lakehouse
Fabric Data Warehouse
Data Pipelines
Real-Time Analytics
OneLake
Power BI Integration
Design Medallion Architecture (Bronze, Silver, Gold layers) within Microsoft Fabric.
Drive Fabric deployment strategies, performance optimization, and environment governance.
Implement Fabric security, access controls, lineage, monitoring, and data lifecycle management.
Azure Data Platform Architecture
Design and implement enterprise data solutions using:
Azure Data Factory (ADF)
Azure Data Lake Storage Gen2 (ADLS)
Azure Synapse Analytics
Azure Ke

📌 Data Architect – Microsoft Fabric (India)
🏢 EXL
📍 India