Senior Data Engineer

Jobtailor; Pune District; On-site; INR 2,000,000 - 3,600,000; Full time

Job summary

Jobtailor is seeking an experienced Data Engineer to design and maintain modern data platforms on Microsoft Fabric Lakehouse, covering Bronze to Gold layers, and enabling scalable ingestion and analytics.

You will build Spark/PySpark pipelines, implement data quality and governance, and collaborate with Architects and BI teams to deliver secure, trusted data assets for Power BI and Direct Lake consumption.

Qualifications

• 5+ years of data engineering experience with hands-on Azure / Microsoft Fabric.
• Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.
• Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.
• 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

• 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

Skills

Data Engineering

Spark / PySpark

Python

SQL

Delta Lake

ETL/ELT

CDC

Data Ingestion Pipelines

Data Quality Checks

Schema Validation

Power BI

Tools

Microsoft Fabric

OneLake

Azure DevOps

Git

CI/CD

Purview

Job description

• 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

Requirements

• 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

Core Competencies

Demonstrates expertise in developing and maintaining Microsoft Fabric Lakehouse solutions, including data ingestion, transformation, and quality frameworks. Proficient in utilizing Spark, PySpark, Python, and SQL for scalable data processing and implementing data governance standards.

Highest-signal resume keywords

• Microsoft Fabric Lakehouse
• Spark / PySpark
• Data Ingestion Pipelines
• Data Quality Frameworks
• Power BI Semantic Models

ATS Optimization Keywords

Hard Skills

• Data Engineering
• ETL/ELT
• CDC
• Data Transformation
• Schema Validation
• Error Handling
• Data Quality Checks
• SQL
• Python
• Delta Lake

Soft Skills

• Collaboration
• Problem-Solving
• Troubleshooting

Industry Keywords

• Commercial Insurance
• Brokerage Data
• Medallion Architecture

Tools & Technologies

• Microsoft Fabric
• Azure DevOps
• Git
• CI/CD
• Power BI
• Microsoft Purview