Description

Key Responsibilities • Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers.

• Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint.

• Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling.

• Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling.

• Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views.

• Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing.

• Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks.

• Support Power BI semantic models and Direct Lake data consumption requirements.

• Implement data quality checks, reconciliation processes, monitoring, and operational controls.

• Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage.

• Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents.

• Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions.

Required Experience &

Skills • 5+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric.

• Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks.

• Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.

• Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.

• Experience developing data quality, validation, reconciliation, and exception-handling frameworks.

• Knowledge of Power BI semantic models and Direct Lake.

• Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment • Commercial insurance or brokerage data experience preferred.

Responsibilities

Key Responsibilities • Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers.





• Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint.

• Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling.

• Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling.

• Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views.

• Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing.

• Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks.

• Support Power BI semantic models and Direct Lake data consumption requirements.

• Implement data quality checks, reconciliation processes, monitoring, and operational controls.

• Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage.

• Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents.

• Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions.

Required Experience &

Skills • 5+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric.

• Robust hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks.

• Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.

• Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.

• Experience developing data quality, validation, reconciliation, and exception-handling frameworks.

• Knowledge of Power BI semantic models and Direct Lake.

• Experience with Microsoft Purview, Azure DevOps, Git, CI/CD,



and deployment • Commercial insurance or brokerage data experience preferred.

Qualifications

Key Responsibilities • Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers.

• Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint.

• Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling.

• Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling.

• Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views.

• Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing.

• Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks.

• Support Power BI semantic models and Direct Lake data consumption requirements.

• Implement data quality checks, reconciliation processes, monitoring, and operational controls.

• Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage.

• Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents.

• Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions.

Required Experience &

Skills • 5+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric.

• Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks.

• Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.

• Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.

• Experience developing data quality, validation, reconciliation, and exception-handling frameworks.

• Knowledge of Power BI semantic models and Direct Lake.

• Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment • Commercial insurance or brokerage data experience preferred.

📌 Fabric Senior Data Engineer (Gurugram)
🏢 EXL
📍 Gurugram