Automate Indeed Job Scraping & Hiring Insights with n8n & Bright Data

Opening Problem Statement

Meet Sarah, a busy recruiter at a mid-sized tech company who spends countless hours sifting through job listings on Indeed for potential hiring signals. She’s overwhelmed by the sheer volume of results and struggles to filter the most relevant roles efficiently. Spending over 8 hours weekly just manually researching wastes valuable time she could dedicate to candidate engagement. Plus, missing out on key roles or hiring trends costs her company potential hires and slows down the recruitment pipeline.

This frustration led Sarah to seek an automated solution that not only scrapes Indeed for specific job postings based on targeted criteria like location, keywords, and company but also assesses the suitability of each role for her company’s hiring goals automatically.

What This Automation Does

This unique n8n workflow harnesses the power of Bright Data’s scraping API and integrates AI-driven language models and Google Sheets, creating a robust job discovery and qualification pipeline. Here’s what happens automatically when you run this workflow:

• Accepts user inputs for precise job search parameters via a custom form trigger, including job location, keywords, and country code.
• Initiates a Bright Data dataset snapshot extraction to fetch fresh Indeed job listings matching the criteria within the last 24 hours, ensuring up-to-date results.
• Polls and checks the scraping snapshot progress asynchronously, waiting until data is ready to retrieve results efficiently.
• Appends all scraped job postings data to a Google Sheets template automatically for easy visualization and tracking.
• Splits job postings into individual records and uses an AI language model (OpenAI GPT-4o-mini) to evaluate each job’s relevance fit for specific hiring needs, outputting simple YES/NO decisions.
• Updates the Google Sheet with AI insights, helping recruiters quickly identify which roles are worth pursuing, saving hours of manual review.

This workflow removes tedious manual searching, centralizes job data, and leverages AI for smart qualification, allowing recruiters like Sarah to focus on what matters: connecting with top talent.

Prerequisites ⚙️

• n8n Automation Platform account (cloud or self-hosted)
• Bright Data API Key for accessing the scraping service 🔐
• Google Sheets account with OAuth2 credentials for updating spreadsheets 📊
• OpenAI API Key configured for GPT-4o-mini model usage 💬
• Optional: Use the provided Google Sheets template for easier start (link included in workflow’s sticky note)

Step-by-Step Guide

Step 1: Set Up the Form Trigger for Job Inputs

In n8n, click + Add Node → search for Form Trigger → select it.

Configure the form with these fields: Job Location, Keyword, and Country (2 letters), marking all as required.

Example: Enter Miami for location, Marketing for keyword, and US for country code.

Save and note the webhook URL generated. Submit a test form to trigger the workflow.

Expected Outcome: The workflow gets triggered with user inputs, starting the automation.

Common Mistake: Forgetting to make fields required or mismatching country code syntax.

Step 2: Configure HTTP POST Request to Trigger Bright Data Scraper

Add an HTTP Request node connected to the form.

Set method to POST and URL to https://api.brightdata.com/datasets/v3/trigger.

In the body (JSON), insert dynamic fields from the form like this:

[
  {
    "country": "{{ $json['Country (2 letters)'] }}",
    "domain": "indeed.com",
    "keyword_search": "{{ $json.Keyword }}",
    "location": "{{ $json['Job Location'] }}",
    "date_posted": "Last 24 hours",
    "posted_by": ""
  }
]

Include headers:
Authorization: Bearer

Expected Outcome: Bright Data receives the scraping request and starts a snapshot job.

Common Mistake: Missing or incorrect API key in headers; ensure to replace with your actual key.

Step 3: Add a Wait Node to Poll for Data Readiness

Insert a Wait node configured to pause the workflow for 1 minute.

This node loops back to check if the Bright Data snapshot is complete, avoiding overload of requests.

Expected Outcome: Workflow waits and polls periodically until data is ready.

Common Mistake: Setting too short or too long wait duration can cause API rate issues or slow responses.

Step 4: HTTP GET Request to Check Snapshot Progress

Connect an HTTP Request node to check snapshot status using the dynamic snapshot ID from the POST response.

Example URL:
https://api.brightdata.com/datasets/v3/progress/{{ $('HTTP Request- Post API call to Bright Data').item.json.snapshot_id }}

Send Authorization header as before.

Expected Outcome: Get JSON reply indicating if snapshot status is “running” or “completed”.

Common Mistake: Referencing snapshot ID incorrectly due to dynamic JSON path errors.

Step 5: Use If Node to Evaluate Snapshot Status

Add an If node checking if the status equals “running”.

If yes, loop back to the Wait node to poll again.

If no (data is ready), proceed to fetch the scraped data.

Expected Outcome: Workflow advances only when data is complete.

Common Mistake: Misconfiguring condition or using incorrect operator causing infinite loops or premature fetching.

Step 6: HTTP GET Request to Retrieve Scraped Jobs Data

Add another HTTP Request node with URL:

https://api.brightdata.com/datasets/v3/snapshot/{{ $('HTTP Request- Post API call to Bright Data').item.json.snapshot_id }}

Query parameter format=json and Authorization header included.

Expected Outcome: Receive the list of job postings as JSON.

Common Mistake: Not including query parameter format or wrong snapshot ID reference.

Step 7: Append Jobs Data to Google Sheets

Use the Google Sheets node set to append operation.

Connect credentials and select the provided template spreadsheet and the first sheet.

The node auto-maps scraped job fields such as company_name, job_title, location, salary_formatted, and more.

Expected Outcome: New job postings appear in your Google Sheet for easy viewing and management.

Common Mistake: Incorrect spreadsheet ID or insufficient permissions cause append failure.

Step 8: Split Out Records for Individual Job Evaluation

Insert a Split Out node to process each job post separately.

This step prepares records for AI assessment one by one.

Expected Outcome: You have individual job entries to analyze.

Step 9: Use LLM Chain Node to Check Job Fit

Add an Chain LLM node configured with this prompt:

Read the following job post:
Company Name {{ $json.company_name }}, job Title:
{{ $json.job_title }},
And job description {{ $json.description_text }}, and tell me if you think I'm a good fit. Answer only YES or NO.

I'm looking for roles in Pfizer

This instructs the AI to determine if the job matches specific hiring needs.

Expected Outcome: For each job, output a simple “YES” or “NO” indicating fit.

Common Mistake: Not configuring the AI credentials or model properly.

Step 10: Update Google Sheets with AI Fit Results

Use another Google Sheets node set to update rows.

Map the AI-generated “AM I a Fit?” field to the corresponding companies.

Expected Outcome: Google Sheets shows job listings annotated with AI fit recommendations, enabling quick decision-making.

Customizations ✏️

• Adjust Date Range for Job Posting: Modify the date_posted field in the HTTP POST JSON body to “Last 7 days” or “Last 3 days” in the Bright Data API call node to get broader or fresher job listings.
• Change Target Company in AI Evaluation: Update the prompt in the Chain LLM node to customize which company or role you want the AI to look for fits with, e.g. replace “Pfizer” with your own employer.
• Switch to Different Job Domains: In the HTTP POST node body, change the domain value from “indeed.com” to another Indeed regional domain like “fr.indeed.com” to scrape jobs from different countries or languages.
• Send Notifications for Fit Jobs: Add an email or Slack node triggered when the AI outputs “YES” to instantly notify a hiring manager or recruiter about promising roles.
• Use a Custom Google Sheets Template: Edit the Google Sheets node to target your own spreadsheet structure or add additional columns for tracking interview stages or candidate notes.

Troubleshooting 🔧

Problem: “401 Unauthorized” API Response

Cause: Invalid or missing Bright Data API key in HTTP Request node headers.

Solution: Go to the HTTP Request node → click the Headers section → update the Authorization header with a valid Bearer token. Test connectivity again.

Problem: Data Not Appearing in Google Sheets

Cause: Incorrect Spreadsheet ID or missing OAuth2 credentials permission.

Solution: Double-check your Google Sheets node settings to ensure you use the right Spreadsheet ID and have Google OAuth correctly connected with write permission.

Problem: Workflow Stuck in Polling Loop

Cause: If the If node condition for “running” status is misconfigured, the workflow may never proceed.

Solution: Verify the If node condition reads exactly {{ $json.status }} == "running" with proper case sensitivity and no extra spaces. Correct it and activate workflow.

Pre-Production Checklist ✅

• Confirm Bright Data API keys are valid and tested.
• Test form submission to ensure triggers work with valid data.
• Validate Google Sheets credentials have write access to your chosen spreadsheet.
• Run the workflow manually to verify data flows from form → Bright Data → sheets → AI cycle.
• Check the AI node is connected and configured with the right model and prompt.
• Review Google Sheets template matches column mappings in the node.

Deployment Guide

Once satisfied with testing, activate the workflow in n8n’s editor by clicking the toggle to “Active.”

Ensure your form webhook URL is publicly accessible for remote triggering by recruiters.

Monitor execution logs in n8n for any errors or API rate information.

You can set up alerting or error notifications using additional nodes if needed to maintain workflow health.

FAQs

Can I use a different web scraping service than Bright Data?

While this workflow is built and tested with Bright Data’s API, you could adapt the HTTP Request nodes to use another scraping provider if they offer a compatible API.

Does this workflow consume OpenAI API credits?

Yes, every AI evaluation call to OpenAI counts toward your subscription or pay-as-you-go usage.

Is my job data secure?

Only you control the Google Sheets and n8n environment access. APIs use secure tokens. Always keep keys confidential.

Can this handle large volume job searches?

Bright Data and n8n can scale, but API rate limits and spreadsheet size may require adjustments for high volume operations.

Conclusion

By implementing this detailed n8n automation, you’ve transformed tedious, manual job scraping and qualification into a seamless, AI-assisted pipeline. Recruiters like Sarah save hours weekly by getting fresh, relevant Indeed job listings enriched with AI fit analysis directly in Google Sheets. This empowers faster decision-making and stronger hiring strategies.

Try expanding this workflow by adding notification nodes to alert on new hiring leads or integrating candidate tracking tools next. Your recruitment workflow just got a significant smart upgrade thanks to n8n, Bright Data, and OpenAI!