Rohith Annadurai

I am an AI-focused Data Engineer with hands-on experience in designing and optimizing scalable data pipelines, real-time data streaming architectures, and cloud-based ML workflows. Proficient in Python, SQL, and AWS services (Glue, Lambda, Kinesis, Redshift), I leverage big data technologies like Apache Spark and Hadoop to process and analyze large-scale datasets efficiently. I am certified as an AWS AI Practitioner and currently pursuing a Master’s in Computer Science at the University of North Texas.

My work is centered on enabling data-driven decision-making through robust ETL frameworks, AI model integration, and automation of end-to-end data workflows.

I have over 2 years of experience as a Data Engineer, specializing in building and optimizing large-scale ETL pipelines, implementing real-time data streaming with AWS Kinesis and Lambda, and automating workflows using Apache Airflow and AWS Glue. I’ve worked extensively with cloud platforms like AWS, big data tools like Spark and Hadoop, and various database systems (SQL, MongoDB, DynamoDB). My work has driven cost reductions, improved data accessibility, and enabled self-service analytics through scalable and fault-tolerant data architectures.

Graduated with a Master’s in Computer Science from the University of North Texas (Jan 2023 – Dec 2024), specializing in data engineering, artificial intelligence, and cloud computing.