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EXL

Senior Data Engineer

EXL

Data Engineer building Microsoft Fabric and OneLake platforms. Developing ingestion, transformation, quality frameworks, and curated datasets for analytics and Power BI.

Posted 9/3/2026full-timeGurugram • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

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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 while adhering to data governance and security standards.

Highest-signal resume keywords
Microsoft Fabric LakehouseSpark / PySparkData Ingestion PipelinesData Quality FrameworksPower BI Semantic Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data EngineeringSQLPythonETL/ELTCDCData TransformationDelta LakeSchema ValidationAudit LoggingException Handling
Tools & Technologies
Microsoft FabricAzure DevOpsGitCI/CDPower BIMicrosoft PurviewData PipelinesSynapse PipelinesNotebooks
Industry Keywords
Commercial InsuranceBrokerage DataData GovernanceRBACPII/PHI Controls

Tech Stack

Tools & technologies
AzureETLGoogle Cloud PlatformPySparkPythonSparkSQL

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • Bachelor's Degree
  • 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

Benefits

Comp & perks
  • No benefits, perks, or compensation extras specified