Compare employer demand
Group advertised roles by company and location to research recruitment activity within a defined market and collection window.
All use casesGlassdoor
HIRING INTELLIGENCE / MANAGED DATA
Glassdoor
job data.
Connect advertised roles, employers and pay context.
We collect Glassdoor job postings with company, location, salary text, job type and descriptions for structured hiring research.
FROM LISTINGS TO HIRING SIGNALS
Bring context to your hiring research.
Study the roles employers advertise, with their job descriptions and location context together. This collection focuses on job postings, not employee reviews or candidate profiles.
Study advertised compensation
Keep salary wording attached to the role, job type and description. Review pay period and currency before building like-for-like comparisons.
Enrich a multi-board view
Add Glassdoor job records to your research alongside other boards, preserving source identifiers rather than assuming every similar role is the same vacancy.
WHAT WE COLLECT
The role. The context.
The original source.
Choose the Glassdoor data points your workflow needs. Related fields stay together, with the final schema and availability confirmed for your collection scope.
Listing identity
Keep each posting traceable to its platform and original page.
View field names
WebsiteJob IDURL
Role & employer
Connect the advertised job title with the company named in the listing.
View field names
Job TitleCompany
Location
Compare hiring across cities, states and countries without losing the source location.
View field names
CityStateCountry
Pay & employment
Retain the salary wording and job type when available. Missing pay is not a zero salary.
View field names
SalaryJob Type
Job description
Preserve the role description for requirements, responsibility and skills research.
View field names
Job Description
Posting & collection time
Keep the listed posting date separate from the collection timestamp. Agree timezone conventions before delivery.
View field names
Date PostedCacheTime
Need standardized titles, parsed salary ranges or skills labels? We can scope these as enrichment, while keeping source values separate.
Plan your schemaBEFORE THE DATA BECOMES A DECISION
Salary context matters. So does what is missing.
A salary string is useful context, but not a verified compensation package. Preserve the evidence before turning it into a number or comparison.
- Do not assume salary provenance
- A salary field alone does not establish whether pay was employer-provided or estimated. Do not label it as confirmed employer pay unless the collected source supports that distinction.
- Keep missing fields explicit
- Salary and job type are not guaranteed on every posting. Preserve unavailable values and avoid inferring employment type from a title alone.
- Keep the product scope clear
- Job postings are this feed. Employee reviews, employer ratings, benefits datasets and candidate information are not silently bundled into it.
A COLLECTION BUILT AROUND YOUR BRIEF
From target roles
to a maintained feed.
A useful job dataset needs defined coverage, source-specific collection and quality checks. We agree each part around your research.
- 01 / DEFINE
Set your market
Share target countries, locations, employers or role criteria. Agree required fields, permitted access and refresh frequency.
- 02 / VALIDATE
Review the evidence
Check a sample for identifiers, missing values, descriptions and salary wording. Confirm matching rules and any enrichment separately.
- 03 / DELIVER
Connect your workflow
Choose CSV, TSV, JSON or a scoped API integration. Agree delivery, monitoring and maintenance before the recurring feed begins.
Need to analyze a few public pages?
The self-service Scraping API collects accessible public content with optional AI analysis. It does not bypass CAPTCHA or login and does not automatically return this job-data schema.
DETAILS THAT CHANGE THE ANALYSIS
Build on the data.
Not assumptions.
Does this include employee reviews or employer ratings?
No. This collection covers job postings and their listed company information. Employee reviews, aggregate ratings and standalone salary reports are different datasets and need separate feasibility and scope review.
Are all salary values employer-provided and comparable?
No such assumption is made. We preserve the source salary wording and validate currency, pay period and provenance where available. Missing or ambiguous information stays explicit. Any numerical normalization is agreed separately.
Can Glassdoor and Indeed jobs be merged into one feed?
We can scope a shared delivery schema and cross-board matching. The source and original ID remain attached to each record. A matching company name and title are not enough to guarantee a single vacancy, so match rules and uncertainty are agreed before consolidation.
How are coverage, refresh frequency and cost agreed?
We scope countries, employers or search criteria, required fields, expected volume and delivery frequency together. We review a sample and agree coverage and pricing before a recurring collection begins. An accessible sample does not establish complete board-wide coverage.
What happens if a page fails or the source changes?
We agree validation, freshness checks and failure reporting as part of the managed service. An unavailable page or incomplete run is reported separately from an empty result. Maintenance and retry responsibilities are defined in the project scope.
Can we receive the data in our existing schema?
We can scope CSV, TSV or JSON delivery and project-specific API integration. Identifiers remain strings; timestamp conventions, null values, description formatting and salary transformations are agreed before delivery. This is a managed feed, not an automatic output schema of the self-service Scraping API.
YOUR MARKET. YOUR DATA REQUIREMENTS.
Build your
Glassdoor
job-data feed.
Tell us which roles, employers and locations matter. We will review access and scope a sample before agreeing scale and delivery.
- Markets, employers and role criteria
- Source fields and optional enrichment
- Refresh schedule and delivery format
Projects are accepted individually, subject to feasibility and available capacity. An enquiry does not reserve a solution or confirm delivery. Pricing and terms are agreed directly with our team.
A real person reviews your brief and follows up about scope and delivery.
ScrapingBuddy is an independent data service, not affiliated with or endorsed by Glassdoor. We provide job-data collection, not recruitment or job placement. Hero artwork is illustrative. Access, coverage and delivery commitments are agreed per project.