Jobberman Scraper - Nigeria Job Listings

What does Jobberman Scraper do?

Jobberman Scraper extracts structured job data from jobberman.com — including salary data, apply URLs, company metadata, and full descriptions. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company profiles) where the source provides them.

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Key features

• ♻️ Incremental mode — recurring runs emit only NEW / UPDATED / REAPPEARED records — UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff. Pair with notifications for daily "new jobs" alerts to your hiring team. Saves 80–95% on daily monitoring.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + notifyOnlyChanges for daily "new Jobberman jobs" pings to your hiring channel.
• 🔗 Paste-mode — paste any jobberman.com URL straight from your browser — single-job pages, search-results URLs, or category SEO URLs. Build the search you want in the UI, copy the URL, paste it here.
• 📋 Detail enrichment — two-stage mode: list, then enrich each job with the full description + detail-page fields (apply counts, education, etc.). One toggle, no extra orchestration.
• 📦 Compact mode — AI-agent and MCP-friendly compact payloads with core fields only — pipe straight into your ATS, salary-benchmarking tool, or LLM context without parsing extras.
• 📝 Description format selection — pick a single description representation — text, html, or markdown — and the unused variants are dropped from each record. Halves payload size when your pipeline only consumes one format.
• 📤 Export anywhere — Download the dataset as JSON, CSV, or Excel from the Apify Console, or stream live via the Apify API and integrations (Make, Zapier, Google Sheets, n8n, …).
• 📧 Email + phone extraction — every record carries extractedEmails[] and extractedPhones[] regex-pulled from the description — direct-outreach lists with no extra processing step.
• 🔗 URL + social-profile extraction — every record carries extractedUrls[] and structured socialProfiles { linkedin, twitter, github, … } parsed from the description — useful when employers drop their careers page or recruiter LinkedIn in-line.
• 💰 Structured salary — salary parsed into structured salaryMin / salaryMax / salaryCurrency / period — no string parsing on your side. Includes salaryHidden flag when the source filtered against a bracket but the listing itself doesn't disclose.

What data can you extract from jobberman.com?

Each result includes Core listing fields (jobId, jobKey, title, location, category, industry, experienceLevel, and experienceRequirement, and more), detail fields when enrichment is enabled (description, descriptionHtml, descriptionLength, and detailFetched), apply information (applyUrl, externalApplyUrl, and easyApply), and company metadata (company and companyUrl). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions and company profiles where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• query — Keyword query for Jobberman search. Use a JSON array string only if you want multiple keyword runs in one actor input.
• country — Jobberman market to search. Current implementation supports Nigeria. (default: "NG")
• location — Location slug or label such as lagos, abuja, remote, or rest-nigeria. Use a JSON array string only if you want multiple locations.
• jobFunction — Job function slug such as engineering-technology, software-data, or accounting-auditing-finance. Use a JSON array string for multiple values.
• industry — Industry slug such as it-telecoms, construction, or manufacturing-warehousing. Use a JSON array string for multiple values.
• experience — Experience filter for Jobberman. (default: "mid-level")
• startUrls — Optional direct Jobberman search or detail URLs. Useful for replaying a known search path or a single listing.
• maxResults — Maximum total job listings to return across all search sources. Use 0 for unlimited. Memory profile: up to 500 results uses 512 MB, above 500 uses 1024 MB. If both maxResults and maxPages are set, the lower cap wins. (default: 25)
• maxPages — Maximum Jobberman search result pages to scrape per search source. Defensive safety bound — maxResults is the primary record cap. If both maxResults and maxPages are set, the lower cap wins. (default: 5)
• includeDetails — Fetch each Jobberman detail page for full description, salary metadata, dates, and apply URL. (default: true)
• includeCompanyProfile — Reserved for later company profile enrichment. Current implementation does not fetch dedicated company pages yet. (default: false)
• descriptionMaxLength — Truncate description to this many characters. Use 0 for no truncation. (default: 0)
• ...and 20 more parameters

Input examples

Basic search — Keyword-driven search scoped to a city with a tight radius.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "engineer",
  "location": "lagos",
  "maxResults": 50
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "engineer",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "engineer-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "query": "engineer",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
  "jobId": "52d14c86fdf489491543c69d876b1b3825bf5eab4066161bb49ef6386898b2ab",
  "jobKey": "site-engineer-n9pxrm",
  "title": "Site Engineer",
  "company": "MEP Insights Ltd",
  "companyUrl": null,
  "location": "Lagos",
  "category": "Engineering & Technology",
  "industry": "Energy & Utilities",
  "experienceLevel": "Mid level",
  "experienceRequirement": "3 years",
  "description": "Responsibilities: Supervise and manage on-site construction activitiesInterpret design drawings, supervise implement and update drawings based on site constraintsGive recommendations on works based on...",
  "descriptionHtml": "\n                    <div><b>Responsibilities:</b></div>\n\n<ul class=\"list-disc list-inside\"><li style=\"word-break: break-word;\">Supervise and manage on-site construction activities</li><li style=\"word...",
  "descriptionLength": 1400,
  "salaryText": "NGN 150,000 MONTH",
  "salaryMin": 150000,
  "salaryMax": 150000,
  "salaryCurrency": "NGN",
  "salaryType": "MONTH",
  "employmentType": "FULL_TIME",
  "postedDate": "2026-03-25T00:00:00.000Z",
  "validThrough": "2026-06-23T00:00:00.000Z",
  "portalUrl": "https://www.jobberman.com/listings/site-engineer-n9pxrm",
  "canonicalUrl": "https://www.jobberman.com/listings/site-engineer-n9pxrm",
  "applyUrl": "https://www.jobberman.com/account/customer/sign-up?apply=1215805&tab=login",
  "externalApplyUrl": null,
  "contactEmail": null,
  "sourceUrl": "https://www.jobberman.com/listings/site-engineer-n9pxrm",
  "sourceCountry": "NG",
  "sourceDomain": "www.jobberman.com",
  "searchQuery": "engineer",
  "searchUrl": "https://www.jobberman.com/jobs?q=engineer&location=lagos&experience=mid-level",
  "isSponsored": true,
  "easyApply": true,
  "fetchedAt": "2026-03-31T08:27:38.297Z",
  "scrapedAt": "2026-03-31T08:27:38.297Z",
  "detailFetched": true,
  "contentQuality": "full",
  "extractedEmails": [],
  "changeType": null,
  "trackedHash": null,
  "firstSeenAt": null,
  "lastSeenAt": null,
  "previousSeenAt": null,
  "expiredAt": null,
  "stateKey": null
}

Incremental fields

When incremental: true, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED. Default output covers NEW / UPDATED / REAPPEARED; set emitUnchanged: true or emitExpired: true to opt into the others.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.
• isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape jobberman.com

1. Go to Jobberman Scraper in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set maxResults to control how many results you need.
4. Enable includeDetails if you need full descriptions, company data.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract job data from jobberman.com for market research and competitive analysis.
• Track salary trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Auto-apply or feed apply URLs into your ATS / hiring pipeline.
• Research company hiring patterns, employer profiles, and industry distribution.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape jobberman.com?

Jobberman Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.005 per run
• Per result: $0.001 per job record

Example costs:

• 10 results: $0.01
• 100 results: $0.11
• 500 results: $0.51

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.11	$0.01	$0.10 (90%)	$0.30
15% — moderate broad query	$0.11	$0.02	$0.09 (81%)	$0.60
30% — high-volume aggregator	$0.11	$0.03	$0.07 (67%)	$1.05

Full re-scrape monthly cost at daily polling: $3.15. First month with incremental costs $0.40 / $0.68 / $1.12 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

FAQ

How many results can I get from jobberman.com?

The number of results depends on the search query and available listings on jobberman.com. Use the maxResults parameter to control how many results are returned per run.

Does Jobberman Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Jobberman Scraper with other apps?

Yes. Jobberman Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Jobberman Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Jobberman Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape jobberman.com?

This actor extracts publicly available data from jobberman.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.