n8n Weekly LinkedIn Job Insights: Bright Data + OpenAI + Slack

Get a weekly LinkedIn hiring “market pulse” in Slack—powered by Bright Data + OpenAI + Google Sheets

This n8n workflow scans LinkedIn job postings weekly using Bright Data, extracts skills and any stated pay with OpenAI (GPT-5.6), compares results to prior runs stored in Google Sheets, and posts a clear job-market digest to Slack.

What this workflow does

• Runs on a weekly schedule and sets your target job keyword, location, and scan limits.
• Uses Bright Data to start a keyword-based LinkedIn jobs discovery, then polls until the snapshot results are ready.
• Downloads discovered job posts, removes duplicates and low-quality entries, and trims descriptions while preserving pay-related text.
• Calls OpenAI (GPT-5.6) to extract, per posting: up to 10 concrete skills, experience, remote policy, and any disclosed pay.
• Aggregates skill demand by counting occurrences across postings, normalizes pay into annual figures when possible, and produces market-level summaries.
• Loads the previous scan from Google Sheets to flag rising, falling, new, and dropped skills for the same role and market.
• Writes one row per skill to Google Sheets for trend tracking, then posts a formatted digest (including a brief narrative) to a selected Slack channel.

Use cases

• SaaS operators tracking which skills are trending for a specific role and location.
• Automation engineers building an end-to-end n8n workflow for recurring market research.
• Teams monitoring job-posted pay signals and how compensation disclosures evolve over time.

Technical details

• Bright Data API via HTTP Header Auth: Authorization: Bearer <YOUR_KEY>
• OpenAI using the GPT-5.6 chat model for skill/pay extraction and digest narrative
• Google Sheets for historical comparisons and per-skill trend logging
• Core n8n logic uses nodes such as: if, set, code, wait, slack, split out