·       Design, implement and maintain scalable along with robust data architectures on AWS.

·       Utilize AWS services such as S3, Glue and Redshift for data storage processing and analytics. 

·       Develop and implement ETL processes using Pyspark to extract, transform and load data into AWS data storage solutions.

·       Collaborate with cross-functional teams to ensure seamless data flow across different AWS services.

·       Proven experience as a Data Engineer with a focus on AWS and Pyspark.

·       Strong proficiency in Pyspark for ETL and data processing tasks.

·       Hands-on experience with AWS data services such as S3, Glue and Redshift.

·       Solid understanding of data modeling, SQL and database design.