Ramakrishna Reddy

I’m a Data Engineer with 5+ years of experience building cloud data warehousing solutions using Snowflake, SQL, Python, and ETL/ELT development. I focus on designing scalable data pipelines, building strong data models, and optimizing SQL performance to deliver reliable, high-quality outputs.

In my roles, I’ve built end-to-end ingestion and transformation frameworks using Snowflake Stages, Snowpipe, and Astronomer (Airflow), including automated watcher jobs for real-time intake. I’ve developed and maintained Medallion Architecture (Bronze/Silver/Gold) with dbt (models, tests, macros, snapshots) and used Snowflake capabilities like Streams & Tasks, Time Travel, and performance tuning to reduce latency and improve operational stability.

Recently, I expanded into Generative AI data engineering by building “Agentic AI Data Foundations” for LLM-powered natural language querying. Using Snowflake Cortex (Cortex Search, Cortex Analyst, Cortex Agent) and Semantic Views, I helped enable semantic data access and improved natural language-to-SQL accuracy with prompt engineering, while generating vector embeddings and document chunks to support enterprise-grade RAG and semantic search.

I also prioritize data observability and governance through integrations like Acryl DataHub (metadata management) and Monte Carlo (freshness, schema changes, pipeline anomalies). I’ve been recognized with “Star of the Quarter” twice and successfully delivered regulatory and AI data platforms for global clients including AIG, DTCC, and T. Rowe Price.