👋 Hi there, I'm
Data Engineer & Software Developer
Transforming data into insights with Azure Databricks, AWS, and cutting-edge cloud technologies. Passionate about building scalable data pipelines and delivering high-performance solutions that drive real impact.
Software engineer with expertise in data engineering, cloud platforms, and scalable systems
I'm a Software Engineer currently working at SPV Consulting, where I build and optimize data pipelines using Azure Databricks for gigabyte-scale data processing. My work focuses on creating scalable data workflows across Bronze, Silver, and Gold layers, enabling efficient downstream analytics and machine learning use cases.
Previously, I worked as a Software Development Engineer at Amazon Web Services on the DynamoDB team, where I enhanced the import system to handle 100,000+ S3 objects, reducing import time by 20% for large datasets. I've also contributed to ServiceNow ITSM implementations and built analytics dashboards using SAP Analytics Cloud.
With a Master's in Computer Science from the University of Illinois at Chicago and published research in computer vision, I bring both theoretical knowledge and practical experience to every project. I'm passionate about leveraging cutting-edge technologies to build systems that scale and deliver measurable impact.
Data engineering with Azure Databricks, optimizing ETL pipelines, and building scalable data workflows
Contributed to DynamoDB service, handling multi-TB backups and high-volume data imports at scale
Published paper on real-time object detection using deep learning and neural networks
Natural Language Processing, Computer Vision, Deep Learning, and Artificial Intelligence
SPV Consulting LLC • Marlton, NJ (Remote)
Amazon Web Services • Seattle, WA
I-ConnectResources Inc. • Columbus, OH
Incture Technologies • Bangalore, India
Hindustan Unilever Pvt. Ltd • Bangalore, India
Examined 13,000 driving scenarios with 27 attributes such as weather, hour, and profession. Achieved 80% accuracy in predicting acceptability of coupons using logistic regression and decision trees. Created and contrasted 5 machine learning models to optimize model accuracy.
Designed and implemented a search engine restricted to the UIC domain. Scraped and indexed over 3000 web pages and applied text preprocessing and vector space models. Ranked query results using cosine similarity, enabling retrieval across a multi-thousand corpus.
Built an Android app which uses technologies such as deep learning and neural networks to detect objects and people. Processed real-time video streams with Apache Kafka and frame-level analysis. Applied YOLO for object detection and Google API for text-to-speech conversion.
The University of Illinois at Chicago
National Institute of Engineering, Mysore, India
2025
2025
2025
2024