Data Engineer

We are looking for a skilled Data Engineer with hands-on experience in Databricks to build and manage scalable, high-performance data pipelines. The ideal candidate will have strong expertise in big data technologies, cloud platforms, and workflow orchestration to support data science and analytics initiatives. Responsibilities Design, develop, and optimize data pipelines on Databricks for ingestion, transformation, and delivery. Work with large datasets using Databricks, Spark, Hadoop, Hive, and SQL. Automate data workflows and orchestrations using Airflow. Ensure high data quality, reliability, and governance across platforms. Collaborate with data scientists, analysts, and software engineers to enable ML and analytics use cases. Monitor, troubleshoot, and improve data infrastructure performance. Required Skills 4 -8 years of experience in Data Engineering. Mandatory hands-on experience with Databricks in production environments. Proficiency in Python, Spark, Hadoop, Hive, SQL. Experience with Airflow or similar orchestration tools. Strong knowledge of ETL / ELT pipelines, data modeling, and performance optimization. Cloud experience (AWS / Azure / GCP) with data engineering services.