01Overview
Job Description AWS Data Engineer with min of 5 to 7 years of experience. Collaborate with business analysts to understand and gather requirements for existing or new ETL pipelines. Connect with stakeholders daily to discuss project progress and updates. Work within an Agile process to deliver projects in a timely and efficient manner. Design and develop Airflow DAGs to schedule and manage ETL workflows. Transform SQL queries into Spark SQL code for ETL pipelines. Develop custom Python functions to handle data quality and validation. Write PySpark scripts to process data and perform transformations. Perform data validation and ensure data accuracy and completeness by creating automated tests and implementing data validation processes. Run Spark jobs on AWS EMR cluster using Airflow DAGs. Monitor and troubleshoot ETL pipelines to ensure smooth operation. Implement best practices for data engineering, including data modeling, data warehousing, and data pipeline architecture. Collaborate with other members of the data engineering team to improve processes and implement new technologies. Stay up to date with emerging trends and technologies in data engineering and suggest ways to improve the team's efficiency and effectiveness. .
