LinkedIn Company Employees Scraper - Find Any Company's Team
Pricing
from $5.00 / 1,000 results
LinkedIn Company Employees Scraper - Find Any Company's Team
Find employees of any company by searching LinkedIn profiles via Google. No login or cookies required. Returns name, headline, profile URL, and current position.
Pricing
from $5.00 / 1,000 results
Rating
5.0
(1)
Developer
Thirdwatch
Maintained by CommunityActor stats
2
Bookmarked
180
Total users
116
Monthly active users
8 hours ago
Last modified
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LinkedIn Company Employees Scraper
Find every employee at any company on LinkedIn — by company name or LinkedIn URL. No login, no cookies, no Sales Navigator seat. Two modes: Basic for fast name/headline/URL lookups, or Full for deep profile enrichment with work history, education, skills, certifications, and languages.
What data can you extract?
Basic mode (fast, $3 per 1,000 results)
| Field | Description |
|---|---|
fullName | Employee's full name |
headline | Professional headline (e.g., "VP Engineering at Stripe") |
url | LinkedIn profile URL |
experience | Current position title |
sourceCompany | Company you searched for |
Full mode (enriched, $3 per 1,000 results)
Everything in Basic, plus:
| Field | Description |
|---|---|
location | City, region, country |
about | Profile summary / bio |
experience | Full work history — position, company, start/end dates, duration, location |
education | Schools, degrees, fields of study, dates |
skills | All listed skills |
certifications | Credentials with issuer |
languages | Spoken languages |
followersCount | LinkedIn follower count |
profilePhoto | Profile image URL |
publicIdentifier | LinkedIn username slug |
Filter by job title and location
Zero in on the exact employees you need. Filters work in both modes and cost nothing extra — they narrow the search before results are returned.
Title filter examples:
Software Engineer— find all SWEs at a companyVP of Sales— isolate sales leadershipProduct Manager— map the PM org
Location filter examples:
San Francisco— Bay Area employees onlyLondon— UK teamIndia— offshore teams
Combine both: find every "Data Scientist" at Google in "New York".
Input
| Parameter | Required | Default | Description |
|---|---|---|---|
queries | Yes | — | Company names or LinkedIn company URLs. Accepts "Google", "employees at Stripe", or "https://www.linkedin.com/company/anthropic/". |
mode | No | basic | basic for name/headline/URL. full for complete profile enrichment. |
jobTitle | No | — | Filter by job title (e.g., "Software Engineer", "VP Sales"). |
location | No | — | Filter by location (e.g., "San Francisco", "London"). |
maxResults | No | 50 | Max employees per company (up to 2,500). |
Example input
{"queries": ["https://www.linkedin.com/company/anthropic/", "Stripe"],"mode": "full","jobTitle": "Software Engineer","location": "San Francisco","maxResults": 100}
Example output (Full mode)
{"fullName": "Jane Smith","headline": "Senior Software Engineer at Anthropic","url": "https://www.linkedin.com/in/janesmith/","publicIdentifier": "janesmith","location": "San Francisco, California, United States","about": "Building safe AI systems. Previously at Google Brain and DeepMind.","profilePhoto": "https://media.licdn.com/dms/image/...","followersCount": 2450,"experience": [{"position": "Senior Software Engineer","companyName": "Anthropic","startDate": {"year": 2023},"duration": "3 yrs","location": "San Francisco, CA"},{"position": "Software Engineer","companyName": "Google","startDate": {"year": 2019},"endDate": {"year": 2023},"duration": "4 yrs"}],"education": [{"schoolName": "Stanford University","degreeName": "Master of Science","fieldOfStudy": "Computer Science","startDate": {"year": 2017},"endDate": {"year": 2019}}],"skills": ["Python", "Machine Learning", "PyTorch", "Distributed Systems"],"certifications": [],"languages": ["English", "Mandarin"],"sourceCompany": "anthropic"}
Use cases
ABM and account-based sales
Map every decision-maker at your target accounts. Feed 200 company names, filter by "VP" or "Director" or "Head of", and get a ready-to-sequence prospect list in minutes. No ZoomInfo contract, no Sales Navigator seat.
Recruiting and talent sourcing
Find every engineer, designer, or PM at a competitor. Use the title filter to isolate "Staff Engineer" or "Principal Designer", then enrich with Full mode for education and tenure. Build targeted sourcing pipelines without LinkedIn Recruiter.
Competitive team intelligence
Track how competitors staff their teams. Run monthly to detect headcount growth, new hires in key functions, and org structure changes. Compare engineering-to-sales ratios across your competitive set.
Market research and investor due diligence
Profile portfolio companies' leadership teams. Track C-suite changes, average tenure, educational backgrounds. Cross-reference with job posting data to identify hiring surges or contractions.
CRM enrichment
Bulk-refresh contact records at named accounts. Detect who left (profiles no longer show the company), who joined (new matches), and who got promoted (title changes). Schedule weekly runs to keep your CRM current.
Compared to alternatives
vs. ZoomInfo / Apollo / Cognism / Lusha ($5K–$50K/year) Same "every employee at this account" data, live from public LinkedIn, at $3/1K results with Full enrichment. No annual contract, no seat license, no minimums. Raw JSON you own.
vs. LinkedIn Sales Navigator (~$99/seat/month) Sales Navigator caps daily searches and profile views, ties lists to a personal account, and charges per seat. This actor needs no LinkedIn account at all and returns structured JSON at API scale.
vs. HarvestAPI LinkedIn Company Employees ($1.50–$12/1K) We match their Full mode data depth (work history, education, skills, certifications, languages) at $3/1K — cheaper than their $8/1K Full tier. Basic mode at $3/1K includes headline parsing. No login or cookies required by either.
Limitations
- Returns profiles that appear in public search results — not an exhaustive org chart. LinkedIn caps public visibility.
- Full mode adds ~3-5 seconds per profile for enrichment. A 100-employee Full mode run takes ~5-8 minutes.
- Very common company names (e.g., "Apple") may include false positives. Use the LinkedIn company URL for maximum precision.
- Title and location filters use Google search operators — they're good but not exact-match. Occasional false positives.
Tips for best results
- Use LinkedIn company URLs for precision —
https://www.linkedin.com/company/stripe/beats"Stripe". - Combine title + location filters to narrow results before they're returned (saves credits).
- Start with Basic mode to validate your query returns the right people, then switch to Full for enrichment.
- Batch companies in one run — the actor handles multiple companies efficiently with rate limiting between each.
Pairs well with LinkedIn Profile Scraper (for ad-hoc profile lookups) and Career Sites Scraper (cross-reference open roles at target companies).
Last verified: 2026-05
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