An Upwork job post prints the buyer's record beside the budget: total spent, hire rate, hires. Our Upwork scraper collects both halves of the public posts in your scope.
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Tell us which part of the freelance market you watch - a list of skills, categories such as Web Development or Digital Marketing, a client country, a budget floor - and how often you need it. We write the crawler, operate it and keep it working when Upwork changes its pages. You receive rows, not a tool to run yourself.
Upwork places a browser challenge in front of its job pages, so rendering, pacing, proxy rotation and CAPTCHA handling are included. We read only what an anonymous visitor is shown: no account, no Connects, no proposals sent. The first step is a free assessment of your scope, and a sample of real posts can be ordered before the first full run.
Every public post has an address under /freelance-jobs/apply/ that ends in a tilde and the job id. The id, not the title slug in front of it, is the key of the row. From the post we return:
The client block is what separates Upwork from an ordinary job board. The buyer stays unnamed, yet the purchasing record is printed next to the budget. It matters because a budget is whatever the client typed: a fixed price of a few dollars beside an Expert requirement reads more like a placeholder than a market rate. With the block delivered as columns, such a post can be read against a client history of many hires and a high average rate - or against none at all.
Posts are discovered through the public browse pages. Each skill has a page under /freelance-jobs/ with the open listings for it, and many skills have city variants - the same skill near New York or Los Angeles. A card repeats the core of the post: Hourly or Fixed-price, the posted or renewed time, the budget or the hours needed, duration, experience level and an excerpt behind a See more link. We crawl the skill pages you choose, remove duplicates by job id - one post can sit under several skills - and open each post for the full record.
The second dimension is time. Activity on this job is a live block: the Proposals range climbs, Interviewing and Invites sent move, Hires goes from nothing to one, and Last viewed by client says whether the buyer is still there. Repeated runs store each observed state with a timestamp, so an Upwork jobs dataset shows how fast a post drew proposals and whether it ended in a hire. Skill pages show current openings, so a post that is filled or withdrawn drops off them; the last state we recorded stays in your history.
Two blocks under a post - Other open jobs by this Client and Explore similar jobs on Upwork - give the crawl further addresses, and the first ties several posts to one unnamed buyer.
Upwork calls itself a work marketplace: clients post jobs, freelancers and agencies answer with proposals, and contracts and payments run through the platform. The company grew out of the merger of Elance and oDesk, took the Upwork name afterwards, and trades on Nasdaq as UPWK.
For a data buyer the line that matters runs between public and private. Job posts are public unless the client chooses otherwise, and so are the browse pages that group them by skill and by place. A job the client limits to Upwork members or to invited freelancers never reaches the open pages. Proposals, messages and the identity of whoever was hired belong to signed-in members, and freelancer profiles are the personal pages of individual people.
What makes the public post useful is its vocabulary. Budgets come in two kinds, hourly and fixed-price. Duration and weekly hours are picked from fixed bands, experience level has three values, and competition is shown as a proposals range instead of an exact count. Because clients pick these values from fixed lists, posts from different categories and different months can be compared as they stand, and money is quoted in US dollars whatever the client's country.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →A job post on Upwork is a priced request from a buyer with a visible track record, which makes the feed a live survey of what freelance work costs and who pays for it.
The post does not name the client, so this is market intelligence, not a contact list.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt builds and runs crawlers as a managed service and hands over the result as a dataset with field documentation. Job boards are a steady part of that work, and Upwork is the one where a post carries a price and a buyer's record instead of a salary and an employer name. We collect job posts and public market data only: nothing from behind the sign-in, and no lists or dossiers of freelancers. Runs are one-off or on the schedule you set - daily, weekly or on demand.
Yes. The ScrapeIt Upwork API returns job id, title, category, job type, budget or hourly range, experience level, skills, the proposals range and the client block as JSON from an endpoint we host, refreshed on the schedule you set. Those rows can also arrive as CSV or Excel files, as a JSON feed or as a load into your database.
Yes. Public job posts with their budgets, skills, activity counters and the unnamed client record are open to any visitor without an account. We collect only publicly available data - everything a visitor can see on Upwork - and we collect it legally. We never log in, and freelancer profiles are left out by default.
Yes. Fixed-price budgets, hourly rate ranges, total spent and the average hourly rate a client has paid are all quoted in US dollars, wherever the client is based. We store amounts as numbers with a currency column and keep the low and the high end of an hourly range in separate fields.
No. The service covers job posts and the market data printed on them; freelancer profiles are personal data, and we do not sell lists or dossiers of freelancers. The client block on a post is a different matter: it carries no name, only location, spending and hiring figures, so it stays in the dataset.
Daily is the sensible minimum. A post is short-lived: the Proposals range fills up, Interviewing and Hires change, and once the job is filled or withdrawn it drops off the skill pages. A daily run catches the post while it is open and stores the activity counters with a timestamp at every pass.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Upwork data from €169/month. Free project assessment, reply within 1 business day.
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