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.

Key Responsibilities :

- Lead the design, development, and implementation of enterprise-scale data solutions using Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), and Azure SQL technologies.

- Design and develop scalable batch, micro-batch, and near real-time data ingestion and processing pipelines.

- Build and optimize ELT/ETL frameworks leveraging Synapse Pipelines, Dedicated SQL Pools, Serverless SQL Pools, Spark Pools, PySpark, and SQL-based transformations.

- Drive the implementation of modern data platform architectures, including Data Lakehouse, Medallion Architecture, and enterprise data warehouse solutions.

- Implement data quality frameworks, validation rules, reconciliation checks, and monitoring controls.

- Lead and mentor teams of Data Engineers, promoting engineering excellence and best practices.

- Implement CI/CD pipelines using Azure DevOps, GitHub, and infrastructure automation tools.

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.

Required Qualifications :

- Bachelor's Degree in Computer Science, Engineering, Information Systems, or related discipline.

- 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 hands-on expertise with PySpark, Spark SQL, Python, and T-SQL.

- Experience implementing Data Vault, Dimensional Modeling, ODS, and Data Warehouse architectures.

- Strong background in Agile delivery methodologies and Azure DevOps.