AWS Data Engineer

Data EngineerThe person on this role will play a crucial role in building scalable and cost-effective data pipelines, data lakes, and analytics systems.Data Ingestion: Implement data ingestion processes to collect data from various sources, including databases, streaming data, and external APIs.Data Transformation: Develop ETL (Extract, Transform, Load) processes to transform and cleanse raw data into a structured and usable format for analysis.Data Storage: Manage and optimize data storage solutions, including Amazon S3, Redshift, and other AWS storage services.Data Processing: Utilize AWS services like AWS Glue, Amazon EMR, and AWS Lambda to process and analyze large datasets.Data Monitoring and Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, cost-efficiency, and scalability.Integration: Collaborate with data scientists, analysts, and other stakeholders to integrate AWS-based solutions into data analytics and reporting platforms.Documentation: Maintain thorough documentation of data engineering processes, data flows, and system configurations.Scalability: Design AWS-based solutions that can scale to accommodate growing data volumes and changing business requirements.Cost Management: Implement cost-effective solutions by optimizing resource usage and recommending cost-saving measures.Troubleshooting: Diagnose and resolve AWS-related issues to minimize downtime and disruptions.Qualifications:Must Have:Strong experience with AWS services on big data platforms.Strong Python experience in building Dash application in AWSSparkShell scripting and Linux knowledgeNice to have:Investment Knowledge preferredLooking for candidates who have worked in Investment/Finance spaceMachine Learning SkillsQualifications:Educational Background: A bachelor's degree in computer science, information technology, or a related field is typically required.A master's degree is preferred with GPA of 3.8+