Microsoft Fabric Data Engineer

EXL; Maharashtra; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Lakehouse Development in India is seeking a data engineer to design and maintain Fabric Lakehouse environments, and to develop and optimize Delta Tables for high-performance analytics. You will implement Medallion Architecture (Bronze-Silver-Gold) to support data quality and governance, and create curated datasets for reporting, analytics, and AI/ML use cases.

You will transform data with PySpark and Spark SQL, build reusable data engineering frameworks, perform cleansing and enrichment, and

Qualifications

• Experience designing and maintaining Lakehouse environments.
• Experience with Delta Tables and analytics data modeling.
• Familiarity with Medallion Architecture and data governance.

Responsibilities

• Design and maintain Fabric Lakehouse environments.
• Develop and optimize Delta Tables for high-performance analytics workloads.
• Implement Medallion Architecture (Bronze, Silver, Gold) for data quality and governance.
• Create curated datasets for reporting, analytics, and AI/ML use cases.
• Develop data transformation logic using PySpark, Spark SQL, and notebooks.
• Create reusable data engineering frameworks and best practices.
• Perform data cleansing, enrichment, and standardization.
• Data Modeling & Analytics Support
• Design dimensional and analytical data models.
• Collaborate with BI teams to support Power BI semantic models and reporting.
• Ensure data consistency, quality, and accuracy across data platforms.

Tools

PySpark

Spark SQL

Delta Lake

Job description

Lakehouse Development

• Design and maintain Fabric Lakehouse environments.
• Develop and optimize Delta Tables for high-performance analytics workloads.
• Implement Medallion Architecture (Bronze, Silver, Gold layers) to support data quality and governance requirements.
• Create curated datasets for reporting, analytics, and AI/ML use cases.

Data Transformation & Processing

• Develop data transformation logic using PySpark, Spark SQL, and notebooks.
• Create reusable frameworks and data engineering best practices.
• Perform data cleansing, enrichment, and standardization activities.
• Data Modeling & Analytics Support
• Design dimensional and analytical data models.
• Collaborate with Business Intelligence teams to support Power BI semantic models and reporting requirements.
• Ensure data consistency, quality, and accuracy across data platforms.