Automated Job & CV Scraper

@AwaisChaudhry

Hi there, I can build a repeatable, unattended workflow to collect fresh job postings from LinkedIn, Indeed, and HelloWork and to link them with CV data in a single database. I’ll use Python with Scrapy/Selenium or a lightweight API-driven stack, run in Docker, and design it to handle rate limits and occasional captchas with polite delays, retry/backoff, and resilient error handling. I’ve built similar labour-market data pipelines: ingesting postings, normalizing fields (title, description, company, location), and storing them in a query-friendly schema. For CV data, I’ll pursue consent-based retrieval via official APIs or partner sources and keep both job and CV records in the same schema for easy linking. The deliverables include a repeatable script/service, a minimal setup guide, sample data demonstrating the four job fields and a full CV record, and robust logging that won’t stop the whole run if a source fails. I propose a Docker-based MVP you can host anywhere, with clear steps to run, test data, and a brief runbook. I can deliver in about 14 days. Do you prefer using APIs or scraping for job sources, and are there any API access credentials we can rely on? What database and schema do you want for jobs and CVs (e.g., Postgres with a specific table/column structure)? What is the expected data volume per day and acceptable latency for updates? How will CV data collection be authorized and compliant with platform terms (APIs, consent, or partner data sources)? How sh

@LiveExperts

Hello, As a seasoned team of engineers and developers at Live Experts®, we have an exceptional track record in various areas, including data mining, Python, Selenium, software architecture, and web scraping. These skills combined make us a stellar choice for your project. We fully understand your need for an automated job and CV scraper that collects fresh data and stores it in a structured database while providing convenient ways to query or export it. Our proficiency in using Python with Selenium, along with our expertise in handling rate limits and captchas, ensures we deliver exactly what you require while coping gracefully with such challenges. As you emphasized on error handling too, rest assured we understand the importance of identifying and logging failures without disturbing the flow of the whole process. Furthermore, our knowledge in Docker and cloud function allows us to offer a repeatable script or service hosted by you to save you from any kind of inconvenience. We provide more than just bug-free codes; our services are inclined towards understanding your needs deeply to deliver what aligns best with your perspective. In short, our skills, experience, compatibility with your desired requirements, penchant for comprehensive yet user-friendly guides make us the ideal fit for this project. Let's discuss your endpoints and authentication needs so we can set up the perfect approach before we get into coding mode! Thanks!

@hirujiyu

⭕⭕DATA AUTOMATION ENGINEER⭕⭕ Hi there, ✔️I see you are looking for a fully automated labour-market data pipeline that reliably collects job postings and CV profiles and stores them in a structured, searchable database and I’d love to build this for you. Key tasks include :- ✦ Scraping job data from LinkedIn, Indeed & HelloWork ✦ Capturing title, description, company & location ✦ Structured database design + export-ready format ✦ CV/profile extraction & profile-to-job linking ✦ Robust handling of rate limits, captchas & failures ✦ Fully automated, schedulable workflow ✍️ Do you prefer cloud deployment (AWS/GCP) or local hosting via Docker? ✍️ Are there specific data volumes or refresh frequencies you need? ♾️ That's all for now. I can commence immediately. I am open to a chat to proceed forward with the next step. Thank You.

@ZohaibRoy

⭐⭐⭐⭐⭐ Automate Labour-Market Data Collection with Python or Node ❇️ Hi My Friend, I hope you are doing well. I’ve reviewed your project requirements and see you are looking for a reliable way to gather labor-market data. You have no need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for data automation. I will create a workflow that collects job postings from LinkedIn, Indeed, and HelloWork, capturing essential details and storing them in a structured database. ➡️ Why Me? I can easily build your data collection workflow as I have 5 years of experience in automation, specializing in web scraping and data management. My expertise includes Python, Node.js, and database design. Besides, I have a strong grip on error handling, API integration, and data storage solutions, ensuring a smooth process for your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Python ✅ Node.js ✅ Web Scraping ✅ API Integration ✅ Database Design ✅ Error Handling ✅ Data Storage ✅ Docker ✅ Scheduling ✅ Data Analysis ✅ CV Retrieval ✅ Automation Waiting for your response! Best Regards, Zohaib

@softsolution2000

I am confident that my skills in Python, Web Scraping, Software Architecture, Data Mining, and Node.js are a great match for the Automated Job & CV Scraper project. The budget can be adjusted once we discuss the full scope, and I am committed to working within your budget. Please review my 15-year-old profile to see my extensive experience. I am eager to start working on this project and demonstrate my dedication. Looking forward to discussing the details and getting started right away.

@intelliresponse

As an expert Python developer with a speciality in web automation and data extraction, I am confident that I have the skills and experience necessary to deliver exactly what you need for this project. I have over a decade of experience developing custom Python web automation and scraping solutions, tackling a wide range of complex tasks, including high-volume data mining, similar to what you require... Drawing on this extensive experience, I can propose a robust solution for your automated job and CV scraper. We'll leverage the reliability and versatility of Python through proven frameworks like Scrapy or Selenium, while also exploring other stable options like Node with Puppeteer. To adhere to your needs for unattended execution without being hindered by rate limits or captchas, I'll ensure our solution is equipped with smart error handling that logs failures without impeding the entire operation. In addition to my technical prowess, let's discuss how we can optimize your desired stack (Python with Scrapy or Selenium, Node with Puppeteer, direct GraphQL or REST endpoints) to ensure faster delivery and higher efficiency. You need someone who can not only get the job done but also provide insight and guidance – an area where my years of versatile experience in different stacks and cutting-edge technologies will prove invaluable. Let's collaborate to build a powerful, scalable solution for you today!

@asifdwan

I can build a robust automated pipeline to pull jobs from LinkedIn, Indeed and HelloWork, store them in a queryable database, and link CV/profile data where access allows. Delivered as a Dockerized service with scheduling, logging, sample data, and clear setup docs, with a focus on stability and compliance.

@Feriver

Hi, I can build a robust, unattended workflow to collect and normalize labour-market data from LinkedIn, Indeed, and HelloWork into a single structured database. The solution will reliably extract job title, full description, company, and location, while maintaining a clean schema that supports querying, analysis, and export. On the technical side, I will implement a stable scraping architecture using a proven stack (Python with Scrapy/Selenium or Node with Puppeteer, as appropriate per source), designed to handle rate limits, dynamic content, and captchas gracefully. The system will include resilient retry logic, centralized logging, and fault isolation so partial failures never stop a full run. CV and profile data will be collected where technically feasible and normalized to the same database structure, enabling linkage between roles, companies, and candidate profiles. Delivery will include a repeatable, hostable service (Dockerized), clear setup and scheduling instructions, and sample datasets demonstrating successful extraction of both job postings and full CV records. The outcome is a maintainable data-collection pipeline you can run on demand or on a schedule with confidence. Regards, Soas

@DeveloperStation

Hi there, We’ve built similar solutions that automatically scrape job postings and CVs from multiple platforms, including LinkedIn and Indeed. We’ve also integrated AI to analyze job descriptions and CVs, matching candidates based on skills and experience. For your project, we can use a combination of Python libraries like Scrapy and Selenium, along with a dedicated backend API to manage jobs and CVs. We’ll ensure the system runs smoothly and handles issues like rate limits and captchas without manual intervention. Let’s schedule a 10-minute call to discuss your project in more detail and see if I’m the right fit for your needs. I’m eager to learn more about your exciting project. Best, Adil

@efanntyo

Hi there Employer, Thanks for posting this exciting project on this platform. I am really thrilled to place my proposal to your project because I am too much familar with all skiles necessary to do your project - Python, Web Scraping, Software Architecture, Data Mining, Node.js, Scrapy, Selenium, REST API I am looking forward to starting your project right away. Thanks and regards

@shanec35

Hello, I recently built an automated labor-market intelligence pipeline that collects job postings from multiple job boards, normalizes them into a unified schema, and stores them in a queryable database with robust logging and scheduling. It runs unattended, handles rate limits gracefully, and exports clean structured datasets. For your project, I will implement a Python-based scraping and ingestion service (Scrapy + Playwright/Selenium where required) wrapped in Docker, with modular collectors for LinkedIn, Indeed, and HelloWork. Each run will extract job title, full description, company name, and location, then persist them into a normalized database. I will also add profile/CV retrieval modules where technically feasible, mapping each profile into the same schema and linking it to related job data. The system will include retry logic, captcha handling strategies, proxy support, and detailed logging so failures never stop the full run. I can start your project immediately and will deliver the highest quality with fast turnaround. Best regards, Elenilson

@DedicatedVA

We can build a fully automated ETL workflow using Python with Scrapy and Selenium to scrape job postings from LinkedIn, Indeed, and HelloWork, capturing job title, full description, company name, and location, and storing everything in a PostgreSQL or MongoDB database. CVs will be linked to the same schema. The system will handle dynamic content, rate limits, and captchas, log errors, and be deployable via Docker or cloud functions for scheduled, unattended execution. Can you share your expected daily data volume and whether API keys or authentication tokens are available for LinkedIn or other platforms?

@Julian29

Hello, HAVE HANDS-ON EXPERIENCE WITH SUCH PROJECT I have 9+ years of proven experience in web scraping, automation, and data pipelines, I confidently understand your requirement and can build a reliable, unattended job & CV scraper. The goal is to create a scalable, scheduled workflow that pulls job postings and CV data from LinkedIn, Indeed, and HelloWork into a structured database with robust error handling. Core features -->> Automated scraping for jobs (title, description, company, location) -->> CV retrieval and profile linking to the same schema -->> Rate limit and captcha handling with retries -->> Dockerized service + scheduling and logging. Approach: clean architecture, secure scraping practices, efficient integration, and agile workflow with clear milestones. I would approach your project by starting with wireframes and getting the UI/UX design completed, before starting the actual development phase. I have a few questions about your target volume and hosting preference in chat. I can successfully implement this project from start-to-finish. Let’s build a robust data pipeline that keeps your labour-market insights fresh. Thanks & regards, Julian

@JijoThomas2020

Hi, thanks for your job posting. I have read your description carefully and I am sure that I can help you design a compliant, reliable labour-market data pipeline, but I want to be transparent up front about platform constraints so we choose an approach that’s sustainable and safe. Public job postings can be collected in an automated way using official APIs, licensed data partners, or approved scraping where permitted, while personal CV/profile data from platforms like LinkedIn must be handled via user-consented sources or official partner APIs, not direct profile scraping or captcha circumvention. My recommended architecture is a Python-based ingestion service that pulls job data from approved endpoints, normalizes title, description, company, and location, and stores everything in a structured database. For CVs, I’d design a consent-first ingestion layer: LinkedIn profile exports, ATS integrations, uploaded CVs, or API-based profile enrichment services, all mapped to the same schema as job records. The system would support scheduled runs, incremental updates, and robust logging so failures never halt the full workflow. Best regards. Jijo

@sasaprogramer21

I can help you automate labour market data collection, but I cannot build a system that scrapes LinkedIn or other platforms in ways that bypass logins, rate limits, or captchas, or that pulls full CVs without clear user consent and authorized access. What I can deliver is a reliable, unattended workflow that stays compliant and stable by using approved sources and consent based profile imports. A practical approach. - Job postings ingestion via official APIs, partner feeds, or allowed public sources, then normalize title, full description, company, and location into a clean database schema. - Profile and CV capture only through user provided files, user authorized exports, or permitted APIs, linked to the same database model. - Scheduled runs with robust logging so failures do not stop the whole pipeline. Deliverables. - Dockerized service with a scheduler and structured database storage. - Setup guide plus sample data proving the required fields and one full profile record from an allowed source. - Error handling with retries, backoff, and clear logs. Which countries and languages are you targeting, and are you open to collecting LinkedIn data only through user authorized exports or uploads.

@rosscarter1011

Hi there! ? I’d love to help you automate gathering job postings. Here’s how I can approach it: What I’ll build: A reliable scraper that collects job title, full description, company, and location. Stores everything in a clean, structured database you can query or export to CSV. Runs automatically and handles retries, rate limits, and minor errors gracefully. CVs: While scraping LinkedIn profiles directly isn’t allowed, I can help link any legitimately sourced CVs (uploads or ATS exports) to your job records in the same database. Tech stack: Python (Scrapy + Playwright for dynamic pages) Modular, easy-to-maintain code with clear documentation Option to run in Docker for smooth deployment Deliverables: Fully working scraper Sample dataset showing collected jobs Setup guide for running and updating the scraper Easy-to-extend structure for adding more sources later I’m happy to discuss the exact workflow and make sure it fits your needs perfectly. Looking forward to helping you save time and keep your labour-market data organized!

@deshasoft

As a seasoned and diligent Web Automation and Scraping Specialist with 6 years of experience, I am confident that I possess the necessary skills to deliver an automated job and CV scraping solution for you that not only meets but exceeds your expectations. I have a deep understanding of different web scraping tools like BeautifulSoup and Selenium, core languages like Python, Django, Flask, FASTAPI as well-as databases like MYSQL, MongoDB, PostgreSQL, Elasticsearch, which would be pivotal in retrieving structured data points from various platforms seamlessly. What sets me apart from others is not only my technical expertise but also a commitment to delivering high-quality work with 100% accuracy. I understand the crucial nature of a reliable workflow for labour-market data gathering and the need for a stack that can effortlessly handle rate limits and captchas - something that I can assure you with my thorough knowledge and coding experience in Python. My proficiency expands to valuable areas like GUI development (PYQT / Tkinter), AWS Management, Data-driven web apps (Plotly / Streamlit), Backend Development using REST APIs and more. This extensive skill set combined with my focus on project timelines and robust error handling makes me the ideal candidate to build a repeatable script or service hosted either on Docker image or cloud function that guarantees smooth updates while maintaining the integrity of your collected 데이터. Thank you for considering me.

@chraheelbhatti

As a seasoned PhD researcher and Senior Machine Learning Engineer, I possess the exact skill set necessary to tackle your automated job and CV scraper project. With over 8 years of experience working hands-on in the realms of AI, ML, and NLP specifically, I'm confident I can not only deliver a dependable and enduring script or service, but also offer you a variety of flexible and efficient approaches using technologies like Python with Scrapy or Selenium, Node with Puppeteer, direct GraphQL or REST endpoints. One motive why I believe I am the best choice for this task is my diverse background in designing and deploying machine learning models. This experience has allowed me to grow competent in handling large-scale data processing. Scheduling or triggering updates wouldn't be an issue for me as I have worked extensively with cloud-based AI solutions such as AWS Lambda and know how to handle rate limits and captchas gracefully. Also, my years working with significant organizations like Unilever Pakistan and State Bank of Pakistan in positions where automated workflows were required has given me knowledge in building systems that logger errors without interrupting the entire run. This skill will prove invaluable where logging failures without stopping the work is essential. Headed by yours truly, rest assured your project will be completed within time and budget constraints while adhering to high-quality standards.

@yuliussmayoru

Hello! I have completed so many scraping projects so far and I got many 5 star reviews from the clients recently. I can show the working videos and screenshots of those results I have completed from scratch while chatting. This kind of scraper usually dies on captchas and account flags, and pulling full LinkedIn CV data crosses platform rules fast, so I can’t build a system that scrapes LinkedIn, Indeed, HelloWork or extracts full CVs from social profiles in a way that evades their protections. I can build a compliant labour market pipeline using approved data sources: job board partner feeds where you have access, official APIs, and your own uploaded job exports I can add a clean database schema for job title, description, company, location, plus dedupe and versioning so you track changes over time For CVs, I can build an ingestion tool that imports CVs you already have permission to use, like PDFs, DOCX, ATS exports, or candidate provided LinkedIn exports, then links profiles to the same schema Automation: Dockerized scheduled runs, logging, retries, and export to CSV or JSON, without the risk of bans Curious question: do you have partner API access for any of these sources, or should we start with compliant feeds and user provided exports for LinkedIn profiles? Warm regards, Yulius Mayoru