Rohith Kalluri

I am a data engineer with 3+ years building and deploying machine learning, deep learning, and NLP solutions in production environments. I focus on creating scalable, reliable data pipelines and AI systems that deliver measurable business impact.

At JP Morgan Chase I designed and maintained Python, SQL, DBT, and Snowflake pipelines that improved ingestion reliability by 40% and reduced end-to-end processing time by 30%. I also optimized data models to increase query performance by 35% and implemented data quality and monitoring processes that reduced errors by 45%.

Previously at Apex infolab I built Airflow-based ETL pipelines, optimized SQL for PostgreSQL and MySQL, and implemented distributed processing with Spark and Dask to accelerate batch workloads. I automated validation and monitoring scripts to improve pipeline reliability and collaborated with ML teams to improve feature readiness.

I bring strong cloud expertise across AWS, GCP, and Azure, deep proficiency with LLM frameworks (Hugging Face, LangChain, OpenAI API), and hands-on experience with model optimization and vector stores. I enjoy working cross-functionally in Agile teams to translate business needs into production-ready data and ML solutions.