EXL - Lead Synapse Data Engineer

Job Summary : The Lead Synapse Data Engineer is responsible for leading the design, development, deployment, and support of enterprise-scale data platforms and analytics solutions using Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, SQL Server, and related Azure services. This role provides technical leadership across data integration, data warehousing, lakehouse implementations, data modeling, and advanced analytics initiatives. The individual will work closely with business stakeholders, architects, data modelers, analysts, and engineering teams to build scalable and governed data solutions supporting reporting, business intelligence, analytics, AI, and data science use cases. The role also includes mentoring and guiding data engineers, establishing engineering best practices, driving platform modernization initiatives, and ensuring the successful delivery of data programs. Required Qualifications : - 10+ years of experience in Data Engineering, Data Integration, Data Warehousing, and Cloud Data Platforms. - 5+ years of hands-on experience with Azure Synapse Analytics. - Strong expertise in Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), Azure SQL Database, and SQL Server. - Extensive experience designing and implementing enterprise-scale ETL/ELT solutions. - Strong hands-on expertise with PySpark, Spark SQL, Python, and T-SQL. - Experience implementing Data Vault, Dimensional Modeling, ODS, and Data Warehouse architectures. - Strong understanding of Medallion Architecture and modern Lakehouse patterns. - Experience working with metadata-driven and parameterized data engineering frameworks. - Expertise in source-to-target mappings, data lineage, data quality, and governance practices. - Strong background in Agile delivery methodologies and Azure DevOps. - Experience with Git-based version control and CI/CD implementation. - Excellent stakeholder management, communication, leadership, and problem-solving skills. Tech Stack : - Azure Synapse Analytics, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), SQL Server, Azure SQL Database, PySpark, Spark SQL, Python, T-SQL, Azure DevOps, GitHub, Databricks