Data Architecture: Develop and maintain scalable data architectures and pipelines on AWS to support data analytics and business intelligence.
ETL Processes: Build and manage ETL processes to extract, transform, and load data from various sources into data warehouses and data lakes.
Data Integration: Integrate data from multiple sources, ensuring data quality, consistency, and security.
Performance Optimization: Optimize data processing workflows for performance, scalability, and cost-efficiency.
Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
Monitoring: Implement monitoring and alerting systems to ensure data pipeline reliability and performance.
Documentation: Maintain comprehensive documentation of data architectures, pipelines, and processes.