Job description

**Role & responsibilities** - Design, develop, and maintain enterprise-scale data pipelines using Azure Databricks. - Develop ETL/ELT solutions using PySpark, Spark SQL, and Delta Lake. - Build and optimize data lake and lakehouse architectures. - Integrate data from diverse cloud and on-premises data sources. - Optimize Databricks workloads for performance, scalability, and cost efficiency. - Implement data governance, security, and quality controls. - Collaborate with architects, analysts, and business stakeholders to deliver data solutions. - Build and maintain CI/CD pipelines for data engineering deployments. - Support real-time and batch data processing requirements. - Troubleshoot production issues and perform root cause analysis. - Mentor junior developers and drive best practices across the team. - Create technical documentation and support enterprise data modernization initiatives.