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Job Description
Design 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.
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