Nishant Choudhary

Co-Founder

Bengaluru, Karnataka, India0 mo experience

Key Highlights

Expert in building scalable web scraping solutions.
Specializes in data extraction from complex websites.
Strong focus on compliance and ethical scraping practices.

Stackforce AI infers this person is a SaaS-focused web scraping expert with strong data engineering capabilities.

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Skills

Core Skills

Web ScrapingData Engineering

Other Skills

AWSAWS EC2AWS LambdaAlgorithmsAmazon DynamodbAmazon ECSAmazon EKSAmazon Web Services (AWS)AnacondaAutomationBack-End Web DevelopmentBeautiful SoupBeautifulSoupBig DataClickHouse

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Dataflirt

Founder

Apr 2024 – Present · 2 yrs 2 mos · Bengaluru, Karnataka, India · Remote

Providing web scraping services to solopreneurs, startups, and enterprises; enabling them build robust data infrastructure.
We cater to the following web scraping stack-
Javascript, Python, Scrapy, Apache Nutch, Selenium, Beautiful soup 4, EC2, S3, DynamoDB, MongoDB, MySQL, Redis, Playwright, Cypress, CheerioJS, Puppeteer, Flask, Docker Kubernetes, ELK
This web crawling and data extraction stack is continuously evolving.
We scrape:
1. Real estate data
2. eCommerce products
3. Company directories
4. SaaS product reviews
5. Hotels & restaurant data
6. Finance websites, Stock market data
7. News content scraping
8. Hospital data
9. Geolocation data
10. Website content
11. Sports data
12. Event and Festival data
In short, anything with accessible domains.

Web ScrapingData ExtractionPythonJavaScriptScrapySelenium+9

Freelance

Web Scraping Python Developer

Jul 2018 – Present · 7 yrs 11 mos · Greater Bengaluru Area · Remote

🛠️ Notable Projects
1. Large-Scale E-commerce Scraping for a Price Intelligence Platform
Scale: ~3,500,000 product pages/day, 300+ domains, 30 parallel Scrapy clusters on AWS
Challenges & Solutions:
🕸️ Heavy anti-bot protection → implemented rotating residential proxies + dynamic browser fingerprinting (Playwright Stealth Mode)
🕸️ High concurrency → leveraged Scrapy + Redis queues to distribute work
🕸️ Pricing accuracy → created Pydantic-based validation on ingestion; stored structured product entities in PostgreSQL & Elasticsearch
Tech Stack: Scrapy, Playwright, Redis, AWS EC2, S3, PostgreSQL, Elasticsearch, Grafana
2. Real-Time Job Data Aggregation
🕸️ Scale: 1.2M listings/day (new/update), Millisecond-level deduplication pipelines
Challenges & Solutions:
🕸️ HTML variability across 60+ career portals → built a “selector-template DSL” using XPath + JMESPath
🕸️ Near-real-time ingestion → async ingestion with aiohttp and Kafka
🕸️ Massive deduplication → implemented locality-sensitive hashing (LSH) + embeddings for fuzzy matching
Tech Stack: aiohttp, FastAPI, Kafka, MongoDB, Polars, Docker
3. Browser-Based Scraping
Scale: 200k navigations/day under Cloudflare + Akamai protection
Challenges & Solutions:
🕸️ Extreme JavaScript rendering → migrated from Selenium to Playwright
🕸️ Session-based bot detection → synthetic browser fingerprints + TLS-fingerprint randomization
🕸️ Resource bottlenecks → custom browser pool with shared Chromium contexts
Tech Stack: Playwright, Python, Kubernetes, Redis, ClickHouse
🚀 What I Specialize In
1. Web Scraping
Distributed crawlers, Browser automation at scale, Anti-bot bypassing (Cloudflare, Datadome, PerimeterX), HTML parsing, extraction heuristics, Proxy management & rotation strategies
Automation, Business process automation, Webhook/REST-based ETL pipelines, Asynchronous data ingestion
2. Data Engineering:
Designing ingestion → transformation → storage flows, High-availability pipelines