Highly motivated Computer Science student with a strong foundation in data engineering, cloud platforms, and advanced analytics. Proven ability to design, build, and deploy scalable ETL pipelines on Microsoft Azure, extract insights from large datasets, and develop data-driven applications. Eager to leverage expertise in Python, SQL, and various data tools to solve complex data challenges and contribute to innovative projects in a dynamic tech environment.
→
B.Tech
Computer Science (e-commerce technology)
Grade: 8.09 CGPA
Issued By
Data Camp
Python, PostgreSQL, Bash.
Pandas, PySpark, Streamlit, RegEx, Airflow, Azure VM, Azure Redis, Azure Data Lake, Docker, Selenium-Stealth, PyFaker, Scikit-learn.
Web Crawling, Web Scraping, ETL Pipelines, API Integration, Automation Scripts, Data Modeling, Database Design, Snowflake.
Basketball (SGFI National-level Player), University Sports Council (Intra-college Leagues Planning & Execution).
Summary
Engineered a fully automated, end-to-end ETL pipeline to autonomously handle the entire data lifecycle for a context-aware BERT sentiment model, addressing the challenge of acquiring a large-scale dataset of over 100,000+ product reviews from Flipkart due to robust anti-scraping measures.
Summary
Designed, built, and deployed a scalable, fully automated, cloud-native ETL pipeline with a user-friendly trigger mechanism to acquire a 350k+ record B2B dataset for supply chain analysis, addressing manual collection infeasibility due to scale and anti-bot measures.