No-code scraping guide

Indeed salary and benefits scraper: export job data

Search public Indeed listings, filter for exposed compensation, and export salary, benefits, skills, work arrangement, company, and application fields.

Opens the matching public Apify Store listing in a new tab.

Checked against the actor

Current inputs and outputs, not generic scraping advice.

Reviewed against the Newbs actor documentation and schema on August 17, 2026. Marketplace behavior and pricing can change, so confirm the live listing before a production run.

Define a comparable market

Salary analysis becomes misleading when roles, countries, currencies, seniority levels, and work arrangements are mixed without labels. Start with one role family and one Indeed country market, then use city, radiusMiles, remoteMode, jobTypes, or experienceLevel only when they support the question.

Keep searchKeyword and searchQuery in the export so every accepted row can be traced to the input that produced it.

Use salary filters carefully

Enable requireSalary when rows without exposed compensation are not useful. minimumAnnualSalary compares normalized annual maximum pay using the selected market's currency, while the raw salary object preserves period, minimum, maximum, currency, estimated status, and annualized values.

Hourly, daily, weekly, and monthly pay can be annualized for comparison, but the raw salaryText should remain available because listing-specific caveats may not fit into numeric fields.

Analyze benefits and skills without inventing data

Benefits, skills, schedules, work arrangement, company fields, and application URLs are returned only when Indeed exposes enough information. Missing arrays or null fields are not evidence that an employer offers no benefits or requires no skills.

Use dataQuality fields to select more complete rows and clearly report how many listings included salary, benefits, descriptions, or company information.

Schedule a recurring hiring report

For new-listing monitoring, sort by date, set postedWithinDays, keep deduplicateJobs enabled, and use a small overfetchFactor unless restrictive filters prevent the actor from filling the requested result count.

Save the tested input as an Apify Task, schedule the run, and process only datasets from successful runs. Inspect OUTPUT whenever a run returns fewer rows than expected.

Read run status before drawing conclusions

EMPTY means Indeed returned a valid search with no jobs. FILTERED means source jobs existed but none passed your filters. CHARGE_LIMIT_REACHED means the user-configured spending cap stopped additional results. FAILED means the source request did not complete.

These statuses prevent a zero-row dataset from being mistaken for zero market demand.

Workflow

Move from a small test to a repeatable data workflow.

Validate the input and output on a small run first. Save a Task, schedule it, or connect the dataset only after the collected fields match the decision you need to make.

  1. Open the Newbs Indeed Jobs Scraper and choose a specific role, country, and optional city.
  2. Start with five to ten results and enable requireSalary only when compensation is essential to the analysis.
  3. Use remoteMode, jobTypes, postedWithinDays, and minimumAnnualSalary to narrow the result set.
  4. Run the actor and inspect salary, benefits, source, and dataQuality fields before exporting.
  5. Save a validated search as a Task for recurring market or recruiting reports.

Filtered salary and remote search

This example requests recent remote software engineering jobs with exposed compensation.

json
{
  "job": ["software engineer"],
  "country": "united states",
  "city": "",
  "numberOfResults": 25,
  "remoteMode": "remote",
  "jobTypes": ["full-time"],
  "requireSalary": true,
  "minimumAnnualSalary": 120000,
  "postedWithinDays": 14,
  "deduplicateJobs": true
}

Compensation and quality fields

Values are examples; the actor does not fabricate fields that Indeed does not expose.

json
{
  "title": "Senior Software Engineer",
  "formattedLocation": "Remote",
  "workArrangement": "remote",
  "salary": {
    "salaryText": "$120,000 - $150,000 a year",
    "annualizedSalaryMin": 120000,
    "annualizedSalaryMax": 150000,
    "currency": "USD",
    "isEstimated": false
  },
  "benefits": ["401(k)", "Dental insurance"],
  "dataQuality": {"hasSalary": true, "hasBenefits": true}
}

Best-fit use cases

These workflows benefit from repeatable cloud scraping, scheduling, dataset exports, and API access.

salary benchmarkingbenefits researchremote hiring analysisjob alertscompany hiring intelligence

Recommended actor

Fetch Indeed job listings with role, company, salary, location, and posting details for hiring intelligence and labor-market research.

View current listing on Apify
Next step

Turn the guide into a repeatable data pipeline.

After the first run, save the input, schedule recurring runs in Apify, and connect the dataset output to your spreadsheet, CRM, dashboard, or AI workflow.

Questions

Frequently asked questions

Does every Indeed listing include salary and benefits?

No. The actor returns those fields only when Indeed exposes them. Use requireSalary and dataQuality when completeness matters.

What does minimumAnnualSalary compare?

It uses normalized annual maximum pay in the selected market's currency. Keep the original salary text and period for review.

How should I interpret an empty dataset?

Inspect OUTPUT. EMPTY, FILTERED, CHARGE_LIMIT_REACHED, and FAILED describe different outcomes and should not be treated as the same result.

Ready-to-run actor

Collect salary and benefits fields when Indeed exposes them

Use the Newbs Indeed Jobs Scraper to search multiple role keywords, apply compensation and work-arrangement filters, and export normalized salary, benefits, skills, company, source, and quality fields.

Run this workflow on Apify

Affiliate disclosure: Newbs may earn a commission from an eligible referral, at no additional cost to you.