Sanket Patekar

Optimized ETL Efficiency: Led data engineering tasks for financial credit ratings, streamlining ETL workflows and improving data integration efficiency by 30% with Python and PySpark. Designed and implemented ETL pipelines using AWS Glue, reducing processing time by 20%. Leveraged AWS services (S3, Lambda, Glue) for customized storage and serverless data processing solutions. Automated job scheduling using step function and Apache Airflow, increasing reliability by 40%. Developed validation scripts that decreased manual checks by 50%. Enhanced query performance by 30% through effective partitioning and indexing strategies. Partnered with cross-functional teams to gather requirements. Maintained 99.9% availability by monitoring and troubleshooting performance issues using AWS CloudWatch. Strengthened data security practices, reducing unauthorized access incidents by 50%.

Designed and implemented a robust data migration framework using AWS Glue. Migrated multi-terabyte datasets from on-premises to AWS cloud, maintaining 100% data security and accuracy. Automated validation and error handling processes, reducing manual intervention by 30%. Collaborated with stakeholders to optimize migration strategies, achieving a 20% improvement in migration efficiency.

Developed a machine learning-based malware detection system for Android applications. Successfully classified applications as malicious or safe. Conducted extensive testing and evaluation, achieving a high detection accuracy rate. Published findings in a peer-reviewed journal.