Otta Scraper

Extract startup and tech job listings from Otta — now part of Welcome to the Jungle — with salary range, equity, tech stack, remote policy, seniority and company funding, using either targeted keyword search or full sitemap enumeration.

• Two collection modes. Search the live Algolia job index for a specific query, or enumerate the entire ~43,000-URL job sitemap for complete coverage.
• Compensation depth. salary.min, salary.max, salary.currency, free-text otherCompensation (such as + Equity) and an explicit salary.hidden flag for employers who deliberately withhold the range.
• Derived seniority. seniorityLevel is computed from required years of experience into Junior, Mid, Senior or Staff/Lead/Principal — you do not have to build that band yourself.
• Built-in buyer filters. Country, remote-only, minimum salary and currency filters are applied in both modes.

Main Use Cases

• Startup job database — build a structured catalogue of startup and tech roles from a live job index
• Job salary benchmarking — map advertised pay ranges by role, seniority, company and location
• Equity compensation data — capture free-text equity and other-compensation notes via otherCompensation
• Tech stack intelligence — aggregate techStack per company to see what a startup actually builds with
• Startup hiring trends analysis — track posted volume, postedAt dates and acceptingApplications over time
• Company funding enrichment — join totalFunding, sectors, companySize and companyHeadquarters onto every role
• Remote job data — isolate remote and remote-only postings with isRemote and remoteOnly

How It Works

1. Mode selection. If query is set, search mode runs. Otherwise sitemap mode runs, enumerating https://app.welcometothejungle.com/sitemap1.xml (~43,000 job URLs). query takes priority over startUrls.
2. Search mode reads Welcome to the Jungle's public Algolia credentials from https://www.welcometothejungle.com/api/env and queries the jobs index directly, paging until your limit or the 1,000-result Algolia pagination cap.
3. Sitemap mode walks the job URLs and parses the embedded Apollo response cache from each page.
4. Each job is flattened into one row with salary, equity, tech stack, locations, seniority, funding and acceptingApplications (derived from live plus the validUntil expiry).
5. Buyer-side filters (country, remoteOnly, minSalary, currency) are applied in both modes. Adaptive rate limiting keeps the crawl polite.

Map the Startup Job Market by Salary, Tech Stack and Funding

Most Otta extractors return a title, a company and a URL. This one returns the fields you actually analyse: a full salary range with currency, free-text other-compensation notes, the technologies the role uses, a derived seniority band, whether the employer hid the salary, and the company's total funding and sectors — so a single run answers "who is paying for senior engineers in London, and how much have they raised?"

Input

Field	Type	Required	Default	Notes
query	string	no	data engineer	Search keywords. Setting it switches the Actor into search mode and takes priority over startUrls.
startUrls	array	no	—	Job URLs or an extra sitemap to enumerate. Objects of the form { "url": "..." }. Only used in sitemap mode.
maxItems	integer	no	100	Maximum jobs to collect. Clamped to 10 on the FREE pricing tier.
maxRequestsPerCrawl	integer	no	120	Request budget for the run.
maxConcurrency	integer	no	8	Parallel requests, clamped to 1–50.
requestsPerSecond	number	no	1.5	Target request rate, clamped to 0.5–20. The Actor throttles adaptively under back-pressure.
country	string	no	—	Country filter. Accepts common aliases such as UK or United Kingdom. Passed to Algolia as a country code in search mode.
remoteOnly	boolean	no	false	Keep only remote roles.
minSalary	integer	no	—	Keep roles whose top of range is at least this value.
currency	string	no	—	Keep roles in this currency. Only filters roles that publish a salary currency.
proxy	object	no	—	Proxy configuration. Not needed on the default path.

Output

One row per job (41 fields):

jobId, externalId, url, applyUrl, title, companyName, companyUrl, team, salary, salaryMin, salaryMax, salaryCurrency, techStack, locations, locationCodes, remoteOnly, isRemote, jobType, subFunction, postedAt, lastSeenAt, validUntil, description, requirements, mission, companyWebsite, companyDescription, companySize, companyHeadquarters, companyIndustry, seniorityLevel, sectors, totalFunding, fundingCurrency, live, acceptingApplications, isInternship, minYearsExperience, maxYearsExperience, originalPostingUrl, crawledAt

salary is an object with min, max, currency, otherCompensation and hidden. salaryMin / salaryMax / salaryCurrency are flat duplicates, convenient for table views and filtering.

Example Input

{
  "query": "software engineer",
  "country": "UK",
  "remoteOnly": true,
  "minSalary": 60000,
  "currency": "GBP",
  "maxItems": 200,
  "requestsPerSecond": 1.5
}

Example Output

{
  "jobId": "1840233",
  "externalId": "wtj-1840233",
  "url": "https://www.welcometothejungle.com/en/jobs/1840233-senior-backend-engineer",
  "applyUrl": "https://boards.greenhouse.io/meridianlabs/jobs/4412087",
  "title": "Senior Backend Engineer",
  "companyName": "Meridian Labs",
  "companyUrl": "https://app.welcometothejungle.com/companies/meridian-labs",
  "team": "Platform",
  "salary": {
    "min": 75000,
    "max": 95000,
    "currency": "GBP",
    "otherCompensation": "+ Equity and 28 days holiday",
    "hidden": false
  },
  "salaryMin": 75000,
  "salaryMax": 95000,
  "salaryCurrency": "GBP",
  "techStack": ["Go", "PostgreSQL", "Kubernetes", "AWS", "gRPC"],
  "locations": ["Remote from UK"],
  "locationCodes": ["REMOTE_UK"],
  "remoteOnly": true,
  "isRemote": true,
  "jobType": "Engineering",
  "subFunction": "Backend",
  "postedAt": "2026-01-28T09:12:00Z",
  "lastSeenAt": "2026-02-10T21:04:00Z",
  "validUntil": "2026-04-30T23:59:00Z",
  "description": "You will own the ingestion pipeline that feeds our clinical trial platform.\n\nRequirements:\n- 5+ years building production backend services\n- Strong Go or Rust experience\n- Comfortable with event-driven architecture\n\nNice to have:\n- Experience in regulated or healthcare data",
  "requirements": ["5+ years building production backend services", "Strong Go or Rust experience", "Comfortable with event-driven architecture"],
  "mission": "Make clinical trial data usable in minutes, not months.",
  "companyWebsite": "https://meridianlabs.io",
  "companyDescription": "Series A healthtech building a clinical trial data platform used by 40 NHS trusts.",
  "companySize": "11-50",
  "companyHeadquarters": "London, United Kingdom",
  "companyIndustry": "Health, Data",
  "seniorityLevel": "Senior",
  "sectors": ["Health", "Data"],
  "totalFunding": 14500000,
  "fundingCurrency": "USD",
  "live": true,
  "acceptingApplications": true,
  "isInternship": false,
  "minYearsExperience": 5,
  "maxYearsExperience": null,
  "originalPostingUrl": "https://boards.greenhouse.io/meridianlabs/jobs/4412087",
  "crawledAt": "2026-02-11T10:02:41.880Z"
}

Pricing

Pay-per-result at $2.50 per 1,000 jobs on the FREE tier. On the FREE tier maxItems is clamped to 10 jobs, so budget a paid tier for real market datasets.

This Actor is priced above the cheapest verified alternative ($2.00 per 1,000), and deliberately so — the extra capability is the point: search mode, sitemap enumeration, equity capture, derived seniority, funding data and proxy-free access.

Integrations & Automation

• Apify API — call from Python, Node or any HTTP client and read the dataset directly.
• Schedules — a daily run tracks new postings and salary movement for a chosen query; a weekly run is enough for hiring-trend analysis.
• Webhooks — push completed runs into a warehouse or alerting workflow.
• MCP — callable by AI agents through the Apify MCP server.

Related Actors

• ahmed_jasarevic/preply-scraper — comparable structured-catalogue extraction for the language tutoring market, if your recruitment research spans both
• ahmed_jasarevic/link-preview-api — enrich company and job URLs with Open Graph and JSON-LD metadata

FAQ

What happened to Otta?

Otta was absorbed by Welcome to the Jungle. Otta URLs redirect, and the live job data now lives on welcometothejungle.com. This Actor reads the current Welcome to the Jungle job index and sitemap, so it keeps working after the merger.

Does Otta have an API?

Not a public documented one. This Actor uses two internal surfaces: the site's public Algolia jobs index for search, and the embedded Apollo response cache on each job page for detail. Search mode reads the public Algolia credentials the site publishes at https://www.welcometothejungle.com/api/env.

When should I use search mode versus sitemap mode?

Use search mode when you want a targeted slice — a role, a country, a salary floor. Use sitemap mode when you want full coverage of the ~43,000-job sitemap. Setting query automatically selects search mode, and query takes priority over startUrls when both are present.

Why do I get fewer than 1,000 results in search mode?

Algolia serves at most 1,000 results for any single query, so maxItems is clamped to that cap in search mode regardless of what you request. To go beyond 1,000 jobs you need sitemap mode.

How is salary.hidden different from a missing salary?

salary.hidden is true when the employer actively concealed the range, which is a meaningful signal about company policy. A job where no salary is published at all has salary: null. Keeping those two cases distinct matters for pay-transparency analysis.

How is seniorityLevel calculated?

It is derived from minYearsExperience: up to 1 year is Junior, up to 3 is Mid, up to 6 is Senior, and above that is Staff/Lead/Principal. Jobs with no stated experience requirement return null.

What are alternatives to this actor?

The main alternative is a simpler Otta-focused extractor. Some job data is also available through third-party job APIs, but those return normalised postings rather than the company context — funding, sectors, size, mission — that this Actor includes. Otta itself, Wellfound and LinkedIn are alternative sources rather than equivalent scrapers.

Do I need a proxy?

No. The default configuration needs none. A proxy field is available if you want to add one.

For AI Agents & LLM Apps

Purpose: returns one row per startup/tech job with salary range, equity, tech stack, seniority, remote policy and company funding.

Minimal working input — smallest input that produces a valid run:

{ "query": "data engineer", "maxItems": 5 }

Targeted search variant with buyer filters:

{
  "query": "software engineer",
  "country": "UK",
  "remoteOnly": true,
  "minSalary": 60000,
  "currency": "GBP",
  "maxItems": 100
}

Full-coverage sitemap variant — omit query, raise the request budget:

{
  "maxItems": 5000,
  "maxRequestsPerCrawl": 5000,
  "requestsPerSecond": 1.5,
  "maxConcurrency": 8
}

Output fields — jobId, externalId, url, applyUrl, title, companyName, companyUrl, team, salary, salaryMin, salaryMax, salaryCurrency, techStack, locations, locationCodes, remoteOnly, isRemote, jobType, subFunction, postedAt, lastSeenAt, validUntil, description, requirements, mission, companyWebsite, companyDescription, companySize, companyHeadquarters, companyIndustry, seniorityLevel, sectors, totalFunding, fundingCurrency, live, acceptingApplications, isInternship, minYearsExperience, maxYearsExperience, originalPostingUrl, crawledAt

Behaviors an agent should know

• query switches modes. Set it and you get Algolia search; omit it and you get sitemap enumeration. query wins over startUrls when both are set.
• startUrls items are objects: { "url": "..." }. Passing bare strings will not be read correctly.
• The input schema prefills query with data engineer, which is what the Apify console form sends. Over the API, omitting query or sending an empty string selects sitemap mode, because the Actor only enters search mode when query is non-empty after trimming. For full-coverage runs, send no query and raise maxRequestsPerCrawl.
• Search mode is hard-capped at 1,000 results by Algolia regardless of maxItems.
• On the FREE pricing tier maxItems is clamped to 10.
• minSalary compares against the top of the advertised range (salary.max, falling back to salary.min), not the bottom.
• currency only filters jobs that actually publish a salary currency; jobs with salary: null pass through.
• country becomes an Algolia offices.country_code filter in search mode, and a text match on headquarters plus locations in sitemap mode — so counts can differ between modes.
• salary: null means no salary published. salary.hidden: true means the employer concealed it. Do not conflate them.
• acceptingApplications is derived from live plus validUntil expiry; it is not a raw source field.
• No proxy is required on the default path.

Billing: pay-per-result — $2.50 per 1,000 jobs on the FREE tier, where the FREE tier also limits you to 10 jobs per run.

Legal & Compliance

This Actor is an independent tool. It is not affiliated with, endorsed by, or sponsored by Otta or Welcome to the Jungle.

It reads only publicly accessible job listings and the public sitemap, using the same public search index the website itself uses. It does not bypass authentication, does not attempt to defeat access controls, and rate-limits itself to avoid undue load on the source site.

You are responsible for your own compliance with the source site's Terms of Service and with applicable data-protection law. Job output includes company names, workplace locations and public job descriptions. Note that EU platform obligations (such as GDPR and the EU Platform Work Directive) place specific obligations on parties that build job databases or matching tools — assess your own position before publishing or redistributing this data. Aggregated salary analysis may also attract your jurisdiction's pay-transparency rules.

Please do not use extracted personal data for unsolicited commercial outreach in violation of applicable law, including CAN-SPAM, GDPR or TCPA.

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