Rohan Kumar

Python Developer & Data Engineer with 3.6 years of experience building scalable web scraping and data acquisition platforms. Expertise in large-scale web/app scraping, browser automation, API reverse engineering, proxy rotation, anti-bot bypass strategies, fingerprint management, distributed crawling, and high-volume data extraction. Strong background in designing fault-tolerant scraping architectures, optimizing crawler performance, and developing end-to-end data pipelines that collect, process, and deliver actionable business intelligence.

Engineer, Data Science at Adglobal360 Pvt. Ltd. (2025-03 – Present)

Client: Reckitt Benckiser

• Engineered 100+ production-grade web and mobile app scrapers, enabling reliable large-scale data extraction from dynamic platforms and delivered structured data.
• Leveraged SSL/TLS interception, HTTP proxy instrumentation, network traffic analysis, and Frida-based dynamic instrumentation to reverse-engineer Android APKs, and build scalable mobile data extraction pipelines.
• Implemented automated authentication handling, browser automation, and CAPTCHA-solving using open-source computer vision models to improve scraping success rates.
• Engineered end-to-end automated data Extraction, transformation, and sell-out analytics pipelines for leading e-commerce platforms across the UAE, KSA, and GCC, reducing 90% of manual operational effort.
• Optimized scraper performance by transitioning browser-based workflows to request/API-driven approaches, reducing execution time by up to 90% and proxy costs by 50%.
• Led scraping infrastructure design and a 4-person team for large-scale data collection, implementing rate-limiting, proxy rotation, and anti-bot bypass strategies.

Software Developer at EMSEC Pvt. Ltd. (2022-12 – 2025-03)

• Engineered a scalable dark-web intelligence scraping system with automated scrapers across 20+ dark websites and forums supporting both SPA and traditional architectures.
• Built and maintained RESTful backend APIs using FastAPI for data ingestion, processing, and seamless integration.
• Containerized backend services using Docker Compose (networking, persistent volumes), enabling automated monitoring and alerting systems.
• Designed automated scheduling pipelines using APScheduler for 24/7 continuous data acquisition with built-in failure recovery and alerting.
• Processed large-scale textual datasets using Hugging Face NLP models for cleaning, preprocessing, and sentiment analysis, improving signal quality for downstream threat intelligence workflows.

Minor in Artificial Intelligence – Indian Institute of Technology, Ropar (2024-11 – 2025-11)

B.Tech. in Electronics Engineering – Dr. A.P.J. Abdul Kalam Technical University (2018-07 – 2022-06)