✨ Glassdoor Jobs Scraper

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Welcome to our Glassdoor Jobs Scraper on Apify! Our premium Glassdoor Jobs Scraper enables you to extract millions of job offerings and company data from Glassdoor, one of the largest job and career plattforms worldwide. This robust tool enables you to extract valuable information at scale, perfect for your data projects, business reports, and developing new applications. The Glassdoor Scraper allows you to scrape:

All job listings including key details:

• job id
• posted date
• title
• category
• job type
• experience
• description
• location
• salary range
• skills

Detailed company profiles including:

• company ID
• name
• headquarters
• year founded
• size
• industry
• sector
• overall rating
• CEO rating
• employee reviews
• revenue.

💡 It's easy to get started

1. Create an Apify Account & get your free trial

2. Go to the Inputs Tab on this Scraper

3. Enter Job Listings Urls or Job Page Urls from Glassdoor

4. Press Start

5. Get your results in seconds!

🌱 Output Sample

Full JSON Data Sample

1{
2  "job_id": 1009320992555,
3  "posted_date": "2024-06-13 19:39:02.188643",
4  "days_ago": 3,
5  "title": "Medical Analytics Data Engineer",
6  "category": "Data Engineer",
7  "job_type": "Full-time",
8  "education_level": null,
9  "experience": "1 years",
10  "description": "ROLE SUMMARY Develop data infrastructure for data scientists and ensure appropriate and efficient development of care gap and HCP prioritization models ROLE RESPONSIBILITIES Develop and maintain data infrastructure Design, develop, optimize, and maintain data architecture and pipelines (e.g., feeding medical data sources into data lake for ongoing projects) Partner with product manager and data lead to develop technical architectures for analytical models Identify data inputs needed to conduct analytics (e.g., claims data for unmet need analysis)..",
11  "company_id": 525,
12  "company_name": "Pfizer",
13  "company_rating": 3.9,
14  "location": "New York, NY",
15  "state": "New York State",
16  "country": "United States",
17  "latitude": 40.71417,
18  "longitude": -74.00639,
19  "salary_range": "117300.0 - 195500.0",
20  "salary_min": 117300.0,
21  "salary_avg": 156400.0,
22  "salary_max": 195500.0,
23  "currency": "USD",
24  "salary_period": "ANNUAL",
25  "salary_source": "EMPLOYER_PROVIDED",
26  "skills": [
27    "Drupal",
28    "Node.js",
29    "React",
30    "Google Tag Manager",
31    "Omniture",
32    "English",
33    "Google Cloud Platform",
34    "Taxonomy",
35    "JavaScript",
36    "Clinical trials",
37    "APIs",
38    "Apache",
39    "Kafka",
40    "Data science",
41    "Google Analytics",
42    "Financial acumen",
43    "Communication skills",
44    "Adobe Analytics",
45    "jQuery",
46    "HTML5",
47    "Adobe Target",
48    "Analytics",
49    "Performance marketing"
50  ],
51  "keywords": null,
52  "organic": true,
53  "sponsored_job": false,
54  "sponsored_company": true,
55  "easy_apply": false,
56  "expired": false,
57  "job_url": "https://www.glassdoor.com/job-listing/medical-analytics-data-engineer-pfizer-JV_IC1132348_KO0,31_KE32,38.htm?jl=1009320992555",
58  "company": {
59    "id": 525,
60    "name": "Pfizer Inc.",
61    "headquarters": "New York, NY",
62    "year_founded": 1849,
63    "size": "Unknown",
64    "stage": "UNKNOWN",
65    "industry": "Biotech & Pharmaceuticals",
66    "sector": "Pharmaceutical & Biotechnology",
67    "overall_rating": 3.9,
68    "ceo_rating": 0.57,
69    "ceo_ratings_count": 2322,
70    "recommend_to_friend": 0.72,
71    "compensation_and_benefits_rating": 3.9,
72    "culture_and_values_rating": 3.7,
73    "career_opportunities_rating": 3.6,
74    "senior_management_rating": 3.3,
75    "work_life_balance_rating": 3.7,
76    "logo_url": "https://media.glassdoor.com/sql/525/pfizer-squareLogo-1611768873226.png",
77    "url": "https://www.pfizer.com",
78    "revenue": "$10+ billion (USD)"
79  },
80  "company_logo": "https://media.glassdoor.com/sql/525/pfizer-squareLogo-1611768873226.png"
81}

⬇ Input

If you use this actor on the apify platform, the UI Input interface is quite self explaining but here are some guidelines to help you use it:

Supported Glassdoor Domains

We currently support all Glassdoor domains.

Country	Link	Supported
Argentina	https://www.glassdoor.com.ar	✅
Australia	https://www.glassdoor.com.au	✅
België (Nederlands)	https://nl.glassdoor.be	✅
Belgique (Français)	https://fr.glassdoor.be	✅
Brasil	https://www.glassdoor.com.br	✅
Canada (English)	https://www.glassdoor.ca	✅
Canada (Français)	https://fr.glassdoor.ca	✅
Deutschland	https://www.glassdoor.de	✅
España	https://www.glassdoor.es	✅
France	https://www.glassdoor.fr	✅
Hong Kong	https://www.glassdoor.com.hk	✅
India	https://www.glassdoor.co.in	✅
Ireland	https://www.glassdoor.ie	✅
Italia	https://www.glassdoor.it	✅
México	https://www.glassdoor.com.mx	✅
Nederland	https://www.glassdoor.nl	✅
New Zealand	https://www.glassdoor.co.nz	✅
Österreich	https://www.glassdoor.at	✅
Schweiz (Deutsch)	https://de.glassdoor.ch	✅
Singapore	https://www.glassdoor.sg	✅
Suisse (Français)	https://fr.glassdoor.ch	✅
United Kingdom	https://www.glassdoor.co.uk	✅
United States	https://www.glassdoor.com	✅

Allowed URL formats

Job Listings	Job Pages
https://www.glassdoor.com/Job/data-scientist-jobs-SRCH_KO0,14.htm	https://www.glassdoor.com/job-listing/data-engineer-ipsos-zrt-JV_KO0,13_KE14,23.htm?jl=1009262165891

• urls: (Required) (String Array) Enter your desired job listing or page urls in bulk or as a single url
  
• job_page_level: (Optional) (Boolean) (Default: True) Scrape job pages data for every job from job listings result. Useful if you need more detailed job and company data like ratings, urls, geo locations.
  
• max_items: (Optional) (Number) (Default:100) Enter the number of items you want to be retrieved. Results will be capped to this limit.
  
• max_pages: (Optional) (Number) (Default:1) Enter the number of pages you want the scraper to go trough (Will be regarded only for Listing Urls)

JSON Input Example

If you decide to use this actor from your favourite programming language. This would be a sample JSON input if you use the apify api via CURL, Python, JS etc.

1{
2	"urls": [
3		"https://www.glassdoor.com/Job/data-scientist-jobs-SRCH_KO0,14.htm",
4        "https://www.glassdoor.com/Job/data-engineer-jobs-SRCH_KO0,13.htm",
5        "https://www.glassdoor.com/job-listing/data-engineer-stoneridge-JV_IC1134704_KO0,13_KE14,24.htm?jl=1009324005177"
6	],
7	"max_pages": 1,
8    "max_items": 60,
9    "job_page_level": true
10}

⬆ Output

Overview Table 🔎

Jobs Table 🧑🏽‍🔬

Company Table 🏦

Ratings Table 🏅

Detailed Output Fields

• Job Details:

  • Job ID: Unique identifier for the job.
  • Posted Date: The date and time when the job was posted.
  • Days Ago: Number of days since the job was posted.
  • Title: Title of the job position.
  • Category: Job category or field.
  • Job Type: Type of employment (e.g., Full-time, Part-time).
  • Education Level: Required education level for the job.
  • Experience: Required years of experience for the job.
  • Short Description: Brief summary of the job.
  • Description: Detailed description of the job responsibilities and requirements.

• Company Details:

  • Company ID: Unique identifier for the company.
  • Company Name: Name of the company.
  • Company Rating: Overall rating of the company.
  • Location: Location of the job.
  • State: State where the job is located.
  • Country: Country where the job is located.
  • Latitude: Latitude coordinate of the job location.
  • Longitude: Longitude coordinate of the job location.

• Salary Information:

  • Salary Range: Salary range offered for the job.
  • Salary Min: Minimum salary offered.
  • Salary Avg: Average salary offered.
  • Salary Max: Maximum salary offered.
  • Currency: Currency in which the salary is listed.
  • Salary Period: Salary period (e.g., Annual).
  • Salary Source: Source of the salary information.

• Skills and Keywords:

  • Skills: List of skills required for the job.
  • Keywords: Relevant keywords associated with the job.

• Job Attributes:

  • Organic: Indicates if the job is an organic listing.
  • Sponsored Job: Indicates if the job is a sponsored listing.
  • Sponsored Company: Indicates if the company is a sponsored employer.
  • Easy Apply: Indicates if the job has an easy apply option.
  • Expired: Indicates if the job listing has expired.
  • Job URL: Direct link to the job listing.

• Company Information:

  • Company ID: Unique identifier for the company.
  • Name: Name of the company.
  • Headquarters: Headquarters location of the company.
  • Year Founded: Year the company was founded.
  • Size: Size of the company.
  • Stage: Development stage of the company.
  • Industry: Industry in which the company operates.
  • Sector: Sector of the company.
  • Overall Rating: Overall rating of the company.
  • CEO Rating: Rating of the company's CEO.
  • CEO Ratings Count: Number of ratings for the company's CEO.
  • Recommend to Friend: Percentage of employees who would recommend the company to a friend.
  • Compensation and Benefits Rating: Rating of the company's compensation and benefits.
  • Culture and Values Rating: Rating of the company's culture and values.
  • Career Opportunities Rating: Rating of the company's career opportunities.
  • Senior Management Rating: Rating of the company's senior management.
  • Work Life Balance Rating: Rating of the company's work-life balance.
  • Logo URL: Direct link to the company's logo image.
  • URL: Direct link to the company's website.
  • Benefits: Information about the company's benefits.
  • Revenue: Company's revenue.
  • Company Logo: Direct link to the company's logo image.

🔎 How you could use this job and company data

• Job Market Analysis: Efficiently scrape and analyze large volumes of job postings to understand market trends, popular job categories, and in-demand skills.
• Salary Benchmarking: Extract and compare salary ranges across different job positions and locations to determine competitive compensation packages.
• Company Insights: Gather detailed company information, including ratings, CEO ratings, employee recommendations, and benefits, to evaluate potential employers.
• Recruitment Optimization: Identify and track job postings to optimize recruitment strategies and improve the visibility of job listings.
• Skills Demand Analysis: Collect and analyze the required skills for various job positions to understand current and emerging skill demands in the job market.
• Job Description Parsing: Extract comprehensive job details such as job ID, title, category, job type, experience, and detailed descriptions to automate job posting analysis.
• Location-Based Job Search: Monitor job availability and salary information by location to assist job seekers in finding opportunities in their preferred regions.
• Employer Branding: Analyze company ratings and reviews to help employers understand their brand perception and improve their workplace culture.
• Application Tracking: Track the status of job listings, including whether they are expired, sponsored, or have easy apply options, to streamline job application processes.
• Promotion and Benefits Analysis: Examine the benefits and promotional opportunities offered by different companies to attract and retain talent.

These use cases demonstrate the versatility and value of the scraper in providing detailed job market insights, optimizing recruitment efforts, and enhancing employer branding strategies.

🤖 While the scraper is running

During the run, the actor will output log messages letting you know what is going on at any point. Each message always contains specific information about the process including which url / page the actor is working on.

If you provide invalid inputs to the actor, it will immediately stop with a failure state and output log messages explaining what is wrong. If you are unsure what went wrong feel free to open up an issue in the issue tab.

🔗 Personal Data Protection

The Glassdoor Jobs Scraper is designed to ethically extract only publicly available jobs data and company information, and it does not scrape private user data such as personal email addresses or personal identifiers.

Our scrapers are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our scrapers, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. You can also read our blog post on the legality of web scraping

💬 Feedback and Support

Your satisfaction is important to us! Therefore we are constantly striving to enhance the performance of our Actors.

If you have any technical feedback or encounter any bugs with the Glassdoor Scraper, please create an issue in the Actor’s Issues tab on the Apify Console.

You can also contact us directly for custom integrations or project use cases at business@radeance.com

Thank you and happy scraping!