Mr. Teja Krishna Kota

AI-Enhanced ETL Frameworks for Scalable Cloud Data Warehousing

Abstract:

As data volumes surge across industries, traditional ETL (Extract, Transform, Load) pipelines struggle with scalability, latency, and operational overhead. This talk presents a next-generation approach to ETL design, incorporating Generative AI techniques and intelligent orchestration to optimize performance, automate schema evolution, and enhance data reliability.

Drawing from real-world implementations in the healthcare domain, including enterprise-scale cloud migrations and secure pipeline integrations, this session will explore how AI-powered modules can dynamically adapt transformation logic, identify data quality anomalies, and reduce manual intervention. The talk will cover architecture patterns involving Snowflake, Databricks, Python-based ETL, and AI agents that assist in rule generation, metadata inference, and auto-documentation.

By blending applied intelligence with robust engineering principles, this talk aims to provide a roadmap for organizations looking to modernize their data infrastructure with smart, self-optimizing ETL frameworks. Attendees will gain actionable insights into designing ETL workflows that are not only scalable but also intelligent, secure, and resilient.

Profile:

Teja Krishna Kota is a Senior Data Engineer at Humana, where he focuses on building scalable, secure data pipelines for healthcare analytics and cloud data warehousing. With experience across enterprise data engineering and applied AI, he specializes in ETL modernization using Snowflake, Databricks, and Python. Teja is passionate about leveraging automation and intelligent systems to drive data-driven transformation.