Complex Data Preprocessing and ETL Development

We seek an experienced AWS developer to construct a comprehensive ETL (Extract, Transform, Load) pipeline, focusing on consumer behavior analysis in the consumer industry. The project involves working with a large taxonomy table containing over 5400 rows and transforming this data for effective querying and analysis using AWS Athena. Project Objectives: --ETL Pipeline Development: Develop an automated ETL pipeline that handles a large taxonomy table. The pipeline should extract data from source files, transform it (including generating over 5,400 binary flag columns based on the taxonomy), and load the processed data into an AWS Athena-compatible format. --User Database Creation: Construct a database with unique user identifiers, incorporating binary flags for each taxonomy they are associated with, enabling detailed user behavior analysis. --Data Storage and Management: Efficiently manage large volumes of data using AWS S3, ensuring data integrity, security, and compliance. --AWS Athena Integration: Configure AWS Athena for complex querying of the transformed data, focusing on user behavior and taxonomy associations. --Data Workflow Automation and Monitoring: Automate the data workflow for consistent updates using AWS Glue and other relevant AWS services. Implement monitoring for optimized performance and cost efficiency. Key Responsibilities: **Design and develop a scalable ETL pipeline using AWS Glue, S3, and Athena to handle a large taxonomy table. **Create a sophisticated database schema with over 5400 binary flag columns for taxonomy and user associations. **Implement data transformation processes to generate binary flags for each user-taxonomy association. Automate the ETL process for regular, efficient updates to the dataset. **Optimize large-scale data storage in S3 and ensure efficient query execution in Athena. **Establish robust monitoring and logging mechanisms, ensuring data security and compliance.