Senior Engineer, Data Engineering

• Design, develop, and maintain high-performance ETL/ELT pipelines using PySpark and Spark SQL using cloud-native components in Databricks
• Build and orchestrate data workflows in AZURE.
• Implement hybrid data integration between on-premise databases and Azure Databricks using tools such as ADF, HVR/Fivetran, and secure network configurations.
• Enhance/optimize Spark jobs for performance, scalability, and cost efficiency.
• Implement and enforce best practices for data quality, governance, and documentation.
• Collaborate with data analysts, data scientists, and business users to define and refine data requirements.
• Support CI/CD processes and automation tools and version control systems like Git.
• Perform root cause analysis, troubleshoot issues, and ensure the reliability of data pipelines.