ETL Data / Platform Engineer Experience: 4–8 Years Job Summary We are looking for an experienced ETL Data / Platform Engineer with strong hands-on experience in Databricks to build and maintain scalable data pipelines and data platforms. Key Responsibilities • Develop and maintain ETL/ELT data pipelines using Databricks. • Work with PySpark, Python, and SQL for data processing and transformation. • Integrate data from multiple sources into data lakes and data warehouses. • Develop, optimize, and monitor data pipelines. • Implement data quality checks, error handling, and performance optimization. • Work with cloud platforms such as Azure, AWS, or GCP. • Collaborate with data engineers, architects, and business teams. • Follow Git, CI/CD, and deployment best practices. Mandatory Skills • 4–8 years of experience in Data Engineering / ETL. • Strong hands-on experience with Databricks – Mandatory. • Good experience in PySpark, Python, and SQL. • Strong knowledge of ETL/ELT concepts and data pipelines. • Experience with Data Lake / Data Warehouse. • Experience with Azure, AWS, or GCP. • Good understanding of data integration, data modeling, and data quality. Good to Have • Experience with Azure Data Factory / AWS Glue. • Knowledge of Delta Lake. • Experience with Apache Spark / Kafka. • Experience with Airflow. • Knowledge of CI/CD and DevOps.