Linkedin Data Scraper ( EVERY-THING )

Linkedin data scraper (EVERY-THING) is an all-in-one LinkedIn data scraper that can extract people, companies, posts, jobs, searches, and engagement data from a single, flexible interface. It helps growth, sales, talent, and analytics teams turn LinkedIn activity into structured, queryable data without manual copy-paste or one-off tools.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for Linkedin data scraper ( EVERY-THING ) you've just found your team — Let’s Chat. 👆👆

Introduction

This project bundles multiple LinkedIn endpoints into a single, consistent scraper that works with a simple endpoint selector and a JSON body payload. You choose what you want to scrape (person, company, jobs, posts, searches, or engagement), send the right body, and receive normalized JSON results.

It solves the pain of juggling different tools or writing custom scrapers for each LinkedIn use case. Instead, everything is handled through a predictable API-style interface that you can plug into data pipelines, enrichment workflows, dashboards, or automations.

It’s built for data engineers, growth marketers, recruiters, sales teams, product analysts, and anyone who needs reliable LinkedIn data at scale.

How the AIO LinkedIn Scraper Works

• You set endpoint to one of the supported operations (person data, company data, posts, jobs, search, suggestions, engagement, etc.).
• You send body as a JSON object that matches the required input for that endpoint (for example, profile URLs, query strings, page numbers, or filters).
• The scraper runs the request, handles pagination tokens where needed, and returns structured JSON arrays.
• You can batch process up to dozens of profiles or companies per run using the multi-profile and multi-company endpoints.
• Advanced endpoints let you search jobs, posts, people, and companies with filters, as well as pull comments, reactions, shares, and autocomplete suggestions.

Features

Feature	Description
Single endpoint router	Use one tool and switch behavior via the endpoint argument (e.g., person-data, company-posts, search-jobs).
Person profile scraping	Scrape full public LinkedIn person profiles, including headline, experience, education, and more from a profile URL.
Multi-person batch mode	Send up to 50 LinkedIn profile URLs and return structured person data in a single run (25 recommended for best performance).
Company profile scraping	Extract public company information such as size, industry, description, website, and follower metrics from company URLs.
Multi-company batch mode	Scrape up to 50 company pages in one go, ideal for competitive research or account list enrichment.
Person posts scraping	Fetch posts published by a specific person, with pagination via page and paginationToken for deep timelines.
Company posts scraping	Retrieve company posts with simple page-based pagination, no token management required.
Job search scraping	Mirror LinkedIn job search with filters for location, job type, experience level, posting recency, company, industry, function, and more.
Post search scraping	Search LinkedIn posts by keyword and filter by content type, authors, companies, industries, and mentions.
People and company search	Use LinkedIn’s own search logic to discover people and companies by query and rich filter combinations.
Engagement & suggestions	Pull comments, reactions, reshares of posts, and autocomplete suggestions for companies, people, functions, industries, locations, schools, and services.
Employee count per skill	Estimate how many employees at a company match specific skills or job titles, based on skill keywords and exclusions.

---

What Data This Scraper Extracts

Field Name	Field Description
endpoint	The endpoint you requested (e.g., person-data, company-data, search-jobs).
url	Canonical LinkedIn URL used as input (person profile, company page, or post link).
urls	Array of LinkedIn URLs when using multi-person or multi-company endpoints.
fullName	Person’s full name from their public profile.
headline	Person’s LinkedIn headline (role, seniority, and positioning text).
location	Person’s primary location string from their profile.
about	Person’s “About” section text, if publicly visible.
currentPositions	Array of current roles, including job title, company, start date, and location.
pastPositions	Array of past roles with titles, companies, and time ranges.
education	List of education entries such as schools, degrees, and study periods.
skills	List of skills and endorsements associated with the profile.
companyName	Company’s official name from its LinkedIn page.
companyWebsite	Company website URL if present on the profile.
companyIndustry	Industry category associated with the company.
companySize	Size bracket for the company (e.g., 51–200, 1,001–5,000 employees).
companyFoundedYear	Company founding year, when available.
companyHeadquarters	City and country of the company headquarters.
followersCount	Number of followers for a person or company page (where provided).
postId	Unique identifier of a LinkedIn post.
postUrl	Direct URL to the LinkedIn post.
postText	Main text content of the post.
postMedia	List of attached media (links, images, videos, documents), if available.
postCreatedAt	Human-readable date/time when the post was published.
postTimestamp	Machine-usable timestamp for the post.
likesCount	Number of reactions/likes on a post.
commentsCount	Number of comments on a post.
sharesCount	Number of shared/reposted instances of a post.
jobId	Unique job posting identifier.
jobTitle	Title of the job listing.
jobCompanyName	Company that posted the job.
jobCompanyId	Numeric company ID (URN-derived) backing the job posting.
jobLocation	Location associated with the job.
jobWorkplaceType	Workplace type (On-site, Remote, Hybrid) derived from filter codes.
jobEmploymentType	Employment type (Full-time, Part-time, Contract, etc.).
jobPostedAt	Human-readable posting time of the job.
jobPostedTimestamp	Numeric timestamp for the job posting.
jobEasyApply	Boolean indicating whether the job is Easy Apply.
searchQuery	Keyword query used for search endpoints (jobs, posts, people, companies).
page	Page index requested in search or listing endpoints.
paginationToken	Token used by person posts endpoint for deep pagination.
commentsUrn	URN identifier used to fetch comments for a post.
reactionsUrn	URN identifier used to fetch reactions for a post.
repostsUrn	URN identifier used to fetch reshares for a post.
commentAuthor	Author of a comment (name and profile reference).
commentText	Text content of a single comment.
reactionType	Type of reaction on a post (like, celebrate, support, etc.).
reactor	Information about the person or entity that reacted.
reshareAuthor	Author name and profile for a reshare.
suggestionType	Suggestion category (company, person, function, industry, location, school, service).
suggestionQuery	Input query that generated suggestions.
suggestedName	Name of the suggested entity (company, person, industry, etc.).
suggestedId	Backing numeric ID or URN of the suggested entity.
skillKeywords	Skill or job title keywords used in the employee count per skill endpoint.
skillExplicits	Skill IDs excluded from employee count calculations.
employeeCountPerSkill	Mapping from skill keyword to estimated employee count in a company.
raw	Optional raw backing object for advanced users who need unprocessed fields.

---

Example Output

[
  {
    "endpoint": "person-data",
    "url": "https://www.linkedin.com/in/ingmar-klein",
    "fullName": "Ingmar Klein",
    "headline": "Senior Software Engineer | Distributed Systems | Team Lead",
    "location": "Berlin, Berlin, Germany",
    "about": "Engineering scalable backend systems and mentoring teams in high-growth environments.",
    "currentPositions": [
      {
        "title": "Senior Software Engineer",
        "companyName": "TechNova Systems",
        "companyId": 1234567,
        "location": "Berlin, Germany",
        "startDate": "2020-06-01"
      }
    ],
    "pastPositions": [
      {
        "title": "Software Engineer",
        "companyName": "CloudBridge",
        "startDate": "2017-02-01",
        "endDate": "2020-05-31"
      }
    ],
    "education": [
      {
        "schoolName": "Technical University of Munich",
        "degree": "M.Sc. Computer Science",
        "startDate": "2014-10-01",
        "endDate": "2016-09-30"
      }
    ],
    "skills": [
      "Distributed Systems",
      "Microservices",
      "Kubernetes",
      "Go",
      "TypeScript"
    ],
    "followersCount": 2130,
    "profilePictureUrl": "https://media.licdn.com/...",
    "timestamp": 1680789311000
  }
]

---

Directory Structure Tree

Linkedin data scraper ( EVERY-THING )/
├── src/
│   ├── main.js
│   ├── endpoints/
│   │   ├── person-data.js
│   │   ├── multi-person-data.js
│   │   ├── company-data.js
│   │   ├── multi-company-data.js
│   │   ├── person-posts.js
│   │   ├── company-posts.js
│   │   ├── search-jobs.js
│   │   ├── search-posts.js
│   │   ├── search-people.js
│   │   ├── search-company.js
│   │   ├── post-comments.js
│   │   ├── post-reactions.js
│   │   ├── post-reshares.js
│   │   ├── suggestion-company.js
│   │   ├── suggestion-person.js
│   │   ├── suggestion-function.js
│   │   ├── suggestion-industry.js
│   │   ├── suggestion-location.js
│   │   ├── suggestion-school.js
│   │   ├── suggestion-service-category.js
│   │   └── company-employee-count-per-skill.js
│   ├── lib/
│   │   ├── httpClient.js
│   │   ├── pagination.js
│   │   ├── linkedin-formatters.js
│   │   └── validators.js
│   └── config/
│       └── defaults.json
├── config/
│   ├── input-schema.json
│   └── endpoints-map.json
├── data/
│   ├── examples/
│   │   ├── person-data.json
│   │   ├── company-data.json
│   │   ├── search-jobs.json
│   │   └── search-posts.json
│   └── inputs.sample.json
├── tests/
│   ├── person-data.test.js
│   ├── company-data.test.js
│   ├── search-jobs.test.js
│   └── utils.test.js
├── .env.example
├── package.json
├── package-lock.json
├── LICENSE
└── README.md

---

Use Cases

• Sales teams use it to enrich prospect lists with live LinkedIn profile and company details, so they can prioritize outreach based on role, seniority, and company size.
• Recruiters and talent sourcers use it to search people and jobs, scrape candidate profiles, and monitor new relevant job postings, so they can react faster than competitors.
• Growth and marketing teams use it to track company and personal posts, comments, and reactions, so they can measure engagement and identify high-performing content themes.
• Data and analytics teams use it to pull large volumes of people, company, and job data, so they can build dashboards, market maps, and talent or customer intelligence models.
• Founders and strategy teams use it to monitor competitors’ hiring, posting frequency, and employee skills, so they can spot strategic moves and market shifts early.

---

FAQs

Q1: How do I choose which LinkedIn resource to scrape? You control behavior through the endpoint field in the input. For example, use person-data for a single profile, multi-person-data for multiple profiles, company-data for a single company, search-jobs for job search, or post-comments for comments on a post. Each endpoint has a documented JSON body shape, so once you select the endpoint, you simply provide the required fields.

Q2: What does the body field look like in practice? body is always a JSON object. For a single person profile, you might send { "url": "https://www.linkedin.com/in/ingmar-klein" }. For multiple people, you pass { "urls": [ "...", "..." ] }. For searches, you pass a mix of query, page, and optional filters like experience, jobType, or locationIdsList. The structure is stable and intentionally close to how filters appear on LinkedIn itself.

Q3: How does pagination work for posts and searches? Some endpoints use simple page numbers (e.g., company posts, job search, post search, people search, company search), where each page returns a fixed number of results. The person posts endpoint adds paginationToken: you set page and pass an empty string for page 1, then use the returned token for subsequent pages. This pattern gives you deep access to long timelines while keeping requests predictable.

Q4: Can I run large batches of profiles or companies? Yes, the multi-profile and multi-company endpoints were designed for batching. They can accept up to 50 URLs per run, but for stability and speed it’s recommended to keep batches below 20–25 URLs at a time. That way, you get a good balance between throughput and reliability and can process large datasets in multiple controlled batches.

---

Performance Benchmarks and Results

Primary Metric – Scraping Speed On typical network conditions, a mixed workload of person profiles and company pages processes roughly 80–120 records per hour when using conservative batch sizes and respecting platform limits. Search endpoints (jobs, posts, people, companies) usually return a page of 10–20 items in a few seconds.

Reliability Metric – Run Success Rate With sensible batching (under 25 URLs per multi-call) and realistic paging depths, success rates above 95% are common across endpoints. Occasional failures are usually tied to unavailable profiles, deleted posts, or aggressive rate limiting on extremely large crawls.

Efficiency Metric – Throughput per Run Combining multi-person, multi-company, and search endpoints, it’s realistic to capture several thousand structured records in a single session by chaining multiple runs, without manual intervention. Filters like experience, industryIdsList, functionIdsList, and locationIdsList help keep the returned dataset focused and reduce wasted bandwidth.

Quality Metric – Data Completeness and Precision For public, accessible profiles and companies, key fields such as names, headlines, titles, company info, and job attributes are typically present and well structured. Some profiles that are out of network or heavily restricted may surface as generic entries (e.g., with placeholders instead of full details), but the scraper keeps identifiers and URLs where possible so you can still track or deduplicate them in your data pipeline.

“Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time.” Nathan Pennington Marketer ★★★★★

“Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on.” Eliza SEO Affiliate Expert ★★★★★

“Exceptional results, clear communication, and flawless delivery. Bitbash nailed it.” Syed Digital Strategist ★★★★★