- Designed and implemented data pipelines, increasing efficiency by 30% using AWS Glue and Lambda for ETL processes.- Architected a scalable data lake solution in AWS, enabling storage and retrieval of 2PB+ of data while reducing access latency by 25%.- Collaborated with machine learning engineers to integrate real-time analytics pipelines, improving predictive modeling accuracy by 15%.- Enhanced existing data warehouse loads, resulting in a 40% reduction in processing time by optimizing Redshift queries.- Spearheaded the migration of on-premise data systems to AWS, achieving a 50% cost reduction and improved data availability.- Automated data validation processes with Python scripts, reducing manual errors by 90%.- Led multiple Agile sprints, coordinating with cross-functional teams to deliver projects within deadlines, boosting project success rates by 20%.

- Built and maintained ETL pipelines, facilitating the integration of 50+ diverse data sources into a centralized PostgreSQL database.- Developed data pipelines using Spark and Hadoop, increasing processing speed for large datasets by 35%.- Deployed and maintained a distributed data architecture that supported 1PB+ of agricultural and demographic data.- Partnered with business analysts to translate requirements into robust data models, enhancing reporting accuracy by 25%.- Streamlined data storage and retrieval operations by implementing partitioning and indexing strategies, improving query performance by 40%.- Automated data ingestion workflows with Unix shell scripting, saving 20 hours of manual effort weekly.Conducted peer code reviews, ensuring code quality and adherence to organizational standards.