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.
ResponsibilitiesKey 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.
QualificationsKey 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.
Skills Required
- 5+ years of overall data engineering experience
- Hands-on experience with Azure and Microsoft Fabric
- Experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks
- Proficiency in Spark or PySpark, Python, SQL, and Delta Lake
- Experience with ETL or 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
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
-
Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
-
Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
-
Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
