I worked on a project where the goal was to build a scalable data processing pipeline on AWS to handle large volumes of data and enable real-time analytics for the company's e-commerce platform. As the AWS Data Engineer on the team, I played a crucial role in designing and implementing the infrastructure and data processing workflows." "To achieve the project goals, we leveraged AWS Glue for data extraction, transformation, and loading (ETL) processes, and stored the processed data in Amazon S3. We utilized AWS Lambda functions for serverless computing and automated data processing tasks. We applied data transformation techniques to cleanse and standardize the data, ensuring its quality and consistency. The processed data was then loaded into Amazon Redshift for fast and efficient querying."