Adhithyan Velumani

Data Engineer working with large-scale data platforms and cloud systems. I enjoy building clean, reliable pipelines and simplifying complex data problems. Always curious about tech, automation, and continuous learning.

My Master’s thesis focused on forecasting the aging of lithium-ion batteries using real-world vehicle data. I worked on data preprocessing, feature extraction, and time-series modeling to understand how usage patterns and temperature affect battery health. The goal was to build a reliable approach to predict battery degradation over time.

During my internship, I worked on building and improving data pipelines for large-scale vehicle and sensor data. I focused on data cleaning, validation, and performance optimization using Python and Spark. This experience helped me understand how analytics solutions are built and operated in real-world production environments.

At Cognizant, I worked as a Data Analyst supporting enterprise data systems and reporting solutions. I handled data extraction, transformation, and analysis using SQL and Python, and collaborated with business teams to deliver reliable insights. This role strengthened my foundation in data quality, stakeholder communication, and production support.

At Mindtree, I worked on ETL development and data integration projects for large enterprise clients. I was involved in building and maintaining data pipelines, troubleshooting data issues, and improving performance. This role gave me strong hands-on experience with structured data, databases, and real-world delivery timelines.