About

Pranav Wadekar is a highly skilled Data Engineer with a passion for Application Development and Machine Learning. With a superior understanding of Predictive Model Building and a strong mathematical background, Pranav is always curious about how things work under the hood and is not just driven by the framework. Currently, Pranav is a Member of Technical Staff at shoptimize, where he has been responsible for maintaining a real-time click-stream pipeline using AWS Kinesis, S3, and Lambda. He has also built a highly scalable ETL pipeline with third-party integrations using AWS Redshift, S3, and Apache Airflow. Pranav has also built an Insights Engine from scratch using DBT, DuckDB, and DSL, as well as a distributed Data Mart for business processes to reduce query load time on the data warehouse. He has also built a Attribution Model to figure out which user is attributed to which campaign/channel/source with different types of models. Additionally, he has done POC's on ELK stack, Prometheus for logging and alerting framework. Pranav has also built scalable REST APIs to drive analytical dashboards and measure product features. He has built a data governance framework for batch pipeline using DataDog agent and deployed statistical models for predictive analytics of important KPIs using Auto Arima, ARIMA. Pranav has a Bachelor of Engineering degree in Information Technology from Maeers Maharashtra Institute of Technology and is currently pursuing a Master of Technology in Software Systems from Birla Institute of Technology and Science, Pilani. Pranav's technical skills include Backend, Data Engineering, Software Engineer, AWS, Apache Airflow, Data Warehouse, ML, and ETL. With 1.19 years of relevant experience, Pranav is a highly motivated and skilled Data Engineer with a passion for building scalable and efficient systems. He is always looking for new challenges and opportunities to learn and grow in his field.