AWS Data Engineer Senior with a strong background in AWS, PySpark, and Redshift.
Hands-on experience in building and optimizing data pipelines, developing robust ETL workflows, and leveraging modern data engineering tools and platforms.
Exposure to dbt (Data Build Tool) is a plus, as the role involves collaboration on end-to-end data transformation and modelling workflows.
Design, build, and maintain scalable pipelines using PySpark on AWS.
Knowledge of Databricks on AWS is a must have
Work with AWS services such as S3, Glue, EMR, and Redshift for data storage, transformation, and querying.
Hands-on experience with Redshift, including performance tuning and data modelling. Strong SQL skills with experience in querying and optimizing large datasets.
Manage and monitor data workflows using orchestration tools like Apache Airflow
Knowledge of CI/CD workflows for data engineering projects.
Utilize Git for version control, ensuring proper collaboration and tracking of code changes.
Establish and follow best practices for repository management, branching, and code reviews.
Good to have DBT Exposure -Contribute to DBT transformations and assist in setting up data modeling workflows.
Working experience on Agile and Scrum methodologies
