•
Data Engineering Projects (SQL & Python):
•
Developed ETL workflows using Python and SQL to ingest, transform, and load structured data from multiple sources
•
Performed data transformations using SQL joins, aggregations, filtering, and deduplication
•
Automated end-to-end data processing pipelines using Python for both file-based and database-driven data
•
Optimized SQL queries, improving query performance and reducing processing time by 30%
•
Collaborated with cross-functional teams to identify data issues and resolve performance bottlenecks
•
Ensured seamless data flow and high data quality through validation, reconciliation, and monitoring processes
•
Automation Script Development (Python & SQL):
•
Designed and optimized automation scripts using Python and SQL, improving data processing speed by 40% and reducing error rates by 25%
•
Automated manual data processing tasks using Python, reducing manual intervention by 30% and improving operational efficiency
•
Implemented data validation checks to ensure record count accuracy and data consistency across datasets
•
Built robust error handling and logging mechanisms in Python scripts to improve pipeline reliability and troubleshooting
•
Optimized SQL queries for faster execution and improved data retrieval performance