I receive a lot of requests seeking for help in listing employees of companies. Which is why I am happy to share that the Employee Listing Endpoint is generally available on Proxycurl API today!

It is not easy to launch this endpoint because no publicly available Linkedin page lists all employees. Without a focused page to page, the only way forward is to scrape every (person) profile. That is what we did.

Yes, to launch the Employee Listing Endpoint, we had to:

  1. Scrape every person profile
  2. Implement infrastructure to keep profiles up to date

That brings me to the next point -- how else can you get a list of all employees other than Proxycurl's Employee Listing API Endpoint?

Use Linkedin to list employees

Given that we scrape Linkedin public profiles to power the Proxycurl's Employee Listing Endpoint, it is only natural that Linkedin, the canonical source of these data should be the best way forward to get employee listing data, And for the most part, that is true.

There are two "buts".

  1. It is non-trivial to scrape Linkedin as a logged-in user at scale. It is also not legal.
  2. You are capped at 1000 results per company.

I tried to list all 235,789 employees of Apple.

I tried to list all 235,789 employees of Apple.
I got 100 pages of results, with each page listing 10 profiles.

So, Linkedin works if you do not mind scraping Linkedin with an active login session, abiding by their rate limits and their 1000 profile limit.

Use LinkDB to list employees

LinkDB is our publicly accessible PostgreSQL database populated with people and company profiles.

Before the launch of our Employee Listing API endpoint, I usually shepherd inquiries on the employee listing problem to LinkDB. And yes, you can use LinkDB to list employees and perform very complex queries! I recommend LinkDB if you are looking to perform a complex search such as:

Find me all

  1. who have left Apple in the last 3 months
  2. who is a Software Engineer
  3. And for the simple use case of listing employees, this is the SQL query you can run on LinkDB to get a list of active employees of DigitalOcean.

And this is the SQL query I can run on LinkDB to get results for the complex search above.

SELECT profile_experience.profile_id, profile.first_name, profile.last_name, profile_experience.title
FROM profile_experience
JOIN profile ON profile_experience.profile_id = profile.id
WHERE profile_experience.company_profile_url= 'https://www.linkedin.com/company/digitalocean'
  AND profile_experience.ends_at IS NULL

However, the caveats of LinkDB remains true:

  1. You have to be comfortable with writing SQL. We do not provide support with programming (or writing SQL queries)
  2. LinkDB is beta software, and will likely remain so in perpetuity.
  3. Performance is not guaranteed and we do not offer the service of optimizing LinkDB for customers' (arbitrary) queries.

Use Proxycurl's Employee Listing Endpoint

I will not use LinkDB in my user-facing product. But I will integrate Proxycurl's Employee Listing Endpoint into my product because it checks the following criteria

Proxycurl's Employee Listing Endpoint is

  1. highly-available
  2. predictable (and fast) response
  3. consistent in performance
  4. predictable pricing

With the endpoint, you can list

  1. past employees
  2. present employees
  3. both

All you need is a Linkedin Company Profile URL. Given that Proxycurl is a developer-tool product, let's dive into code. Let's get a list of Clearbit's employees.

Counting Clearbit employees

from pprint import pprint
import requests

api_key = 'YOUR_PROXYCURL_API_KEY'
host = 'https://nubela.co/proxycurl'

api_endpoint = f'{host}/api/linkedin/company/employees/count'

header_dic = {'Authorization': 'Bearer ' + api_key}

response = requests.get(api_endpoint,
                        params={
                            'url': f'https://www.linkedin.com/company/clearbit',
                        },
                        headers=header_dic)
pprint(response.json())

Proxycurl returns 69 active employees.

$ time python employeelisting.py
200
{"total_employee": 69}

real	0m1.814s
user	0m0.176s
sys	0m0.051s

The endpoint takes 1.8s to complete.

But who exactly are the employees?

Let's make another API call, but this time to the /proxycurl/api/linkedin/company/employees/count endpoint

from pprint import pprint
import requests

api_key = 'YOUR_PROXYCURL_API_KEY'
host = 'https://nubela.co/proxycurl'

api_endpoint = f'{host}/api/linkedin/company/employees/'

header_dic = {'Authorization': 'Bearer ' + api_key}

response = requests.get(api_endpoint,
                        params={
                            'url': f'https://www.linkedin.com/company/clearbit',
                        },
                        headers=header_dic)
pprint(response.json())

Here are the results, 69 Linkedin Profiles (truncated).

$ time python employeelisting2.py
{'employees': [{'profile_url': 'https://www.linkedin.com/in/scott-carter-742a876'},
               {'profile_url': 'https://www.linkedin.com/in/adamrutkow'},
               {'profile_url': 'https://www.linkedin.com/in/jared-j-chan-%E2%98%81%EF%B8%8F-31b81273'},
               {'profile_url': 'https://www.linkedin.com/in/asiqur-anik'},
               {'profile_url': 'https://www.linkedin.com/in/jasmine-sabba-b4741329'},
               {'profile_url': 'https://www.linkedin.com/in/bradylemmerman'},
               {'profile_url': 'https://www.linkedin.com/in/ashannetaylor'},
               {'profile_url': 'https://www.linkedin.com/in/ethanhackett'},
               {'profile_url': 'https://www.linkedin.com/in/neil-bartholomay'},
               {'profile_url': 'https://www.linkedin.com/in/colbyaley'},
               {'profile_url': 'https://www.linkedin.com/in/djlumley'},
               {'profile_url': 'https://www.linkedin.com/in/rossmoser'},
               ...]}

real	0m1.010s
user	0m0.164s
sys	0m0.047s

The endpoint takes 1s to complete.

Linkedin says that Clearbit has 108 employees. We have 63 of them. This is expected because

  1. We scrape US Profile only. If Proxycurl have employees outside of the US region, our API will not be able to return them.
  2. Not all Linkedin profiles have public profiles. We can only return public profile results.

Counting Clearbit employees

from pprint import pprint
import requests

api_key = 'YOUR_PROXYCURL_API_KEY'
host = 'https://nubela.co/proxycurl'

api_endpoint = f'{host}/api/linkedin/company/employees/count'

header_dic = {'Authorization': 'Bearer ' + api_key}

response = requests.get(api_endpoint,
                        params={
                            'url': f'https://www.linkedin.com/company/clearbit',
                        },
                        headers=header_dic)
pprint(response.json())

Proxycurl returns 69 active employees.

$ time python employeelisting.py
200
{"total_employee": 69}

real	0m1.814s
user	0m0.176s
sys	0m0.051s

The endpoint takes 1.8s to complete.

But who exactly are the employees?

Let's make another API call, but this time to the /proxycurl/api/linkedin/company/employees/count endpoint

from pprint import pprint
import requests

api_key = 'YOUR_PROXYCURL_API_KEY'
host = 'https://nubela.co/proxycurl'

api_endpoint = f'{host}/api/linkedin/company/employees/'

header_dic = {'Authorization': 'Bearer ' + api_key}

response = requests.get(api_endpoint,
                        params={
                            'url': f'https://www.linkedin.com/company/clearbit',
                        },
                        headers=header_dic)
pprint(response.json())

Here are the results, 69 Linkedin Profiles (truncated).

$ time python employeelisting2.py
{'employees': [{'profile_url': 'https://www.linkedin.com/in/scott-carter-742a876'},
               {'profile_url': 'https://www.linkedin.com/in/adamrutkow'},
               {'profile_url': 'https://www.linkedin.com/in/jared-j-chan-%E2%98%81%EF%B8%8F-31b81273'},
               {'profile_url': 'https://www.linkedin.com/in/asiqur-anik'},
               {'profile_url': 'https://www.linkedin.com/in/jasmine-sabba-b4741329'},
               {'profile_url': 'https://www.linkedin.com/in/bradylemmerman'},
               {'profile_url': 'https://www.linkedin.com/in/ashannetaylor'},
               {'profile_url': 'https://www.linkedin.com/in/ethanhackett'},
               {'profile_url': 'https://www.linkedin.com/in/neil-bartholomay'},
               {'profile_url': 'https://www.linkedin.com/in/colbyaley'},
               {'profile_url': 'https://www.linkedin.com/in/djlumley'},
               {'profile_url': 'https://www.linkedin.com/in/rossmoser'},
               ...]}

real	0m1.010s
user	0m0.164s
sys	0m0.047s

The endpoint takes 1s to complete.

Linkedin says that Clearbit has 108 employees. We have 63 of them. This is expected because

  1. We scrape US Profile only. If Proxycurl have employees outside of the US region, our API will not be able to return them.
  2. Not all Linkedin profiles have public profiles. We can only return public profile results.

We recommend that you use Proxycurl's Employee Listing Endpoint for just US region only

Remember how earlier in the article, I mentioned that the only way we can support the Employee Listing Endpoint is by crawling all profiles in a region. It turns out that we do have limited crawling capacity. Just to give you a sense of what limited means to us. We are talking about scraping millions of profiles a day.

It takes a lot of resources to

  1. Surface all Linkedin profiles of a region
  2. And KEEP them refreshed as best as we can

As such, we have to limit the Employee Listing Endpoint to the US region only. (It does work internationally, but we do not offer any guarantees on the quality of the results.)

How much does Proxycurl's Employee Listing endpoint cost?

Get started with Proxycurl's Employee Listing endpoint today!

You can view the documentation for the

Do give it a spin and if you have any questions, you can always talk to me at st[email protected] . I look forward to your emails and I do reply promptly :)

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