AWS Data EngineerDesign and development: Design, develop, and implement data pipelines using AWS services such as AWS Glue, Lambda, S3, Kinesis, and Redshift to process large-scale data.ETL processes: Build and maintain robust ETL processes for efficient data extraction, transformation, and loading, ensuring data quality and integrity across systems.Data warehousing: Design and manage data warehousing solutions on AWS, particularly with Redshift, for optimized storage, querying, and analysis of structured and semi-structured data.Data lake management: Implement and manage scalable data lake solutions using AWS S3, Glue, and related services to support structured, unstructured, and streaming data.Data security: Implement data security best practices on AWS, including access control, encryption, and compliance with data privacy regulations.Optimization and monitoring: Optimize data workflows and storage solutions for cost and performance. Set up monitoring, logging, and alerting for data pipelines and infrastructure health.Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data needs and deliver data solutions aligned with business goals.Documentation: Create and maintain documentation for data infrastructure, data pipelines, and ETL processes to support internal knowledge sharing and compliance.