Crawling Engineer

Also known as: Web Crawling Engineer, Web Scraping Engineer, Data Acquisition Engineer, Web Data Engineer, Crawler Engineer.

What does a Crawling Engineer do?

A Crawling Engineer is an engineer who builds and runs systems that collect data from the web at large volumes: from thousands of competitor sites to billions of pages for a search index or an AI training corpus. Their job is to collect a lot, refresh it quickly, avoid overspending on proxies and browsers and stay within the law. Typical tasks:

• build distributed crawlers, schedule crawls and remove duplicates;
• write parsers for messy, constantly changing page layouts;
• run proxy and headless browser infrastructure;
• deal with rate limits, captchas and fingerprinting;
• turn raw HTML into clean structured data, and for AI teams also filter and deduplicate the corpus.

When does a company need a Crawling Engineer?

A company needs a Crawling Engineer when data from the open web is the foundation of the product rather than a one-off task: search, price and market monitoring, aggregators, data vendors, AI labs that collect their own training data. Common triggers: a home-grown parser breaks every week, sources have tightened anti-bot protection, volume has to grow tenfold or more, and the proxy bill is already visible in the budget. If there are a few sources that rarely change, a separate role is not needed: a Data Engineer or Backend Developer can handle the parsing, and sometimes it is cheaper to buy the data from a vendor.

Crawling Engineer vs Data Engineer: what's the difference?

A Crawling Engineer differs from a Data Engineer in extracting data nobody hands over voluntarily, while a Data Engineer works with data the company already has or receives through an API. That gives a Crawling Engineer a different set of problems: blocking, captchas, layout changes and the legal limits of collection. What sets them apart from an ML Engineer is their place in the chain: a Crawling Engineer prepares the corpus, an ML Engineer trains models on it.

Why is it hard to hire a Crawling Engineer?

Crawling Engineers are hard to hire because the role has no established title, and only a small number of companies have experience of crawling at scale.

• The same people are called Backend Developer, Data Engineer or Scraping Engineer, and searching by title barely finds them.
• Most candidates have written parsers for a handful of sites; experience crawling billions of pages is rare.
• Candidates often avoid describing part of their experience in detail in a CV because of the sensitive legal side of data collection.
• Engineers who have collected training corpora for AI are in high demand right now and busy.

What to decide before hiring a Crawling Engineer?

• What are you collecting, and at what volume? Thousands of sites and billions of pages need different architectures and a different level of engineer.
• How difficult are the sources? Static pages, heavy JavaScript and strong anti-bot protection call for different experience.
• Where does the data go: search, analytics, a training corpus? For an AI corpus, filtering and quality matter, not only volume.
• Who owns the legal side: robots.txt, terms of use, personal data? If nobody does, the engineer will decide alone and the company will carry the risk.
• Build from scratch or stabilise an existing crawler? The answer determines whether you need an engineer who designs systems or one who fixes things fast.

Where to find a Crawling Engineer?

Crawling Engineers most often come from search engines, price and market monitoring services, data vendors, adtech and AI labs, and from Backend Developers who owned parsing at marketplaces and aggregators. A strong profile signal is open-source crawling tools or a clear sense of scale: how many pages a day the system collected and what one page cost. NEWHR finds such candidates by the results of their work, not by applications to a job post.

How to assess a Crawling Engineer in an interview?

Crawling Engineers are assessed with a review of a data collection system they built and a design task based on a real, difficult source of the company's. The review covers architecture, scale, blocking, layout changes and cost per page. On the company side, the Head of Data or the CTO take part, plus the lawyer responsible for data collection if there is one.

Strong signals:

• knows the cost of collecting one page and how they reduced it;
• describes how the system detected that a parser had started returning junk;
• talks calmly and specifically about the legal and ethical limits of their work.

Red flags:

• solves every problem by buying more proxies;
• gives no thought to the load on other people's sites or their terms of use;
• has experience with only one or two sites and does not think about scale.

How long does it take to hire a Crawling Engineer?

We present the first candidates for the Crawling Engineer role within 5–7 days of the brief.

Related roles

• Data Engineer — builds pipelines for data the company already has or receives through an API.
• ML Engineer — trains models on the collected data.
• AI / LLM Engineer — builds LLM products that often need fresh web data.
• Network Security Developer — works with network protocols and protection from the other side of the fence.