Lead and manage a team of Data Engineers and provide technical guidance and mentorship.
Design, develop, and optimize scalable data pipelines in an on-premise environment.
Build robust ETL/ELT workflows using Python, Spark, SQL, and Airflow.
Design and manage complex Apache Airflow DAGs for data pipeline orchestration.
Develop and optimize Spark-based data processing solutions for large datasets.
Write complex and optimized SQL queries for data extraction, transformation, and analysis.

🎯 Requirements

8+ years of overall experience in Data Engineering.
Strong hands-on experience with Python.
Strong experience with Apache Spark / PySpark.
Advanced SQL skills, including complex joins, CTEs, window functions, subqueries, and optimization.
Strong experience with Apache Airflow for workflow orchestration.
Experience working with on-premise data environments.

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