Posted 31 May, 2026
547517_DNAMFG_Databricks_India
ClifyX
India
Full Time
Reference: 365_594563_26-02843
Role Overview - Databricks:
We are seeking a skilled Databricks Engineer to design, develop, and optimize large scale data processing solutions using the Databricks Lakehouse Platform. The ideal candidate will have strong experience in big data technologies, cloud platforms, and data engineering best practices to enable analytics, machine learning, and data driven decision making.
Key Responsibilities:
• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and Delta Lake
• Build ETL/ELT workflows to ingest, transform, and process structured and unstructured data
• Optimize Spark jobs for performance, scalability, and cost efficiency
• Implement data models and manage data lakes/ lakehouses using Delta tables
• Collaborate with data scientists and analysts to support machine learning and advanced analytics
• Integrate Databricks with cloud services (Azure, AWS, or GCP)
• Ensure data quality, reliability, and governance across pipelines
• Implement CI/CD and version control for Databricks notebooks and jobs
• Monitor jobs, troubleshoot failures, and resolve performance issues
• Follow security and compliance best practices
We are seeking a skilled Databricks Engineer to design, develop, and optimize large scale data processing solutions using the Databricks Lakehouse Platform. The ideal candidate will have strong experience in big data technologies, cloud platforms, and data engineering best practices to enable analytics, machine learning, and data driven decision making.
Key Responsibilities:
• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and Delta Lake
• Build ETL/ELT workflows to ingest, transform, and process structured and unstructured data
• Optimize Spark jobs for performance, scalability, and cost efficiency
• Implement data models and manage data lakes/ lakehouses using Delta tables
• Collaborate with data scientists and analysts to support machine learning and advanced analytics
• Integrate Databricks with cloud services (Azure, AWS, or GCP)
• Ensure data quality, reliability, and governance across pipelines
• Implement CI/CD and version control for Databricks notebooks and jobs
• Monitor jobs, troubleshoot failures, and resolve performance issues
• Follow security and compliance best practices
