The List for Sourcing Websites as well as Data Points Was Given by the Client.



A well-known Job portal from the USA was searching to automate job listings using jobs web crawling across different job boards as well as the company’s job listings.


The client required job listings to get scraped from 20 job websites including Monster, Indeed, and CareerBuilder. Different data points that the client wanted include Job postings like job titles, wages, location, Job descriptions, company profiles, as well as candidate resumes.



The listing of source sites as well as data points was given by this client. They required this data to get scraped on an everyday basis meaning that the latest data needs to be given daily. We had completed web crawling jobs for scraping the necessary data fields from a website list given by this client. These requirements come under website crawling services that are given by us as the crawlers need to set specifically for every website in the listing. The client needed data in the CSV format as well as got uploaded in their Dropbox. When the primary setup was completed, our web crawlers started providing the data that was openly fed into this client’s Dropbox. We had delivered nearly 2 million jobs listed during the initial data crawling as well as around 200K records of well-structured and clean data on an everyday basis.


Setting up the Crawler The crawler was initially configured such that it could automatically scrape product price and essential data fields for present categories on a daily basis.

Data Template : A template was created utilizing data structuring based on the schema provided by the customer.

Delivery of Data : Without any manual input from either side, the closing data was supplied in an XML format through Data API regularly.

The dataset had all the information including comments, news timelines, most viewed articles, customer behaviour, etc. All of the scraped data was indexed using hosted indexing components, and search APIs were made available so that a client could get the results every few minutes.


  • All the difficult technical aspects of web scraping were considered by us
  • It took merely a few days to get the early set up after which the data started coming consistently
  • Our progressive tech stack controlled a huge amount of data naturally
  • The client had improved their job portal using a massive number of listings in the shorter time
  • The data scraped was 20 times more affordable than what an in-house setup might have cost to the client.