Kavithalakshmi Baskar

Building the company's enterprise data platform from scratch, defining architecture, ingestion standards, storage layers, and governance model for engineering and manufacturing data. Designing ingestion and processing pipelines for various engineering data types, including scans, 3D models, JSON telemetry, and configuration files.

Automated ETL pipelines using Python, Snowflake, and dbt, reducing manual intervention and on-call support from 10 hours to 1 hour, boosting team efficiency by 90%. Architected scalable data pipeline infrastructure and engineered batch and real-time data processing workflows, reducing latency by 50%.

Led migration of 150+ clients from on-premises databases to AWS, reducing infrastructure and operational costs by 50%. Enhanced Kubernetes monitoring with Datadog and Docker integration, improving client satisfaction from 50% to 90%.

Automated analytics processes using Stonebranch, reducing manual effort and enhancing workflow efficiency. Orchestrated migration from SQL-based systems to Big Data platforms and architected AWS Aurora database infrastructure.

Led migration to 14SOI technology, reducing model release cycle time by 50% through automated Perl script workflows. Pioneered development of streamlined model generation system enabling automatic builds with minimal parameter configuration.

Master of Science in Electrical Engineering from the University of Connecticut, completed in 2011.