Job Listings Tracker

Overview

This project is a personal job-search pipeline tracker designed to reduce friction in capturing job listings and managing applications. It keeps everything in one place so I can move from discovery to application to follow-up without losing context.

Problem

Job searching involves scattered data:

• Job postings are spread across platforms
• Roles have inconsistent formatting and missing details
• It is easy to lose track of what was applied, what needs tailoring, and when to follow up

Solution

A structured tracking system that:

• Captures job listings into a single database
• Normalizes core fields into a consistent schema
• Tracks application status and next actions
• Enables quick filtering by role, company, location, and priority

Architecture

Pipeline

1. Job listing captured (manual entry or automated ingestion)
2. Normalization layer maps raw listing data into a consistent schema
3. Status tracking updates as the application progresses
4. Follow-up reminders and notes keep the pipeline actionable

Core schema

• Company, Role, Location, Link
• Source, Date added
• Status (Saved, Applied, Interviewing, Offer, Rejected)
• Priority, Notes, Next action, Follow-up date

Tech Stack

• Central store: Airtable or Google Sheets
• Automation layer: n8n (planned or implemented)
• Optional enrichment: GPT for role summarization and fit notes

Results

• Reduced time spent context-switching across tabs and sources
• Faster application turnaround by keeping next steps visible
• Cleaner decision-making with consistent status and priority fields

What’s next

• Auto-ingestion from LinkedIn and job boards via email parsing and saved searches
• GPT-based resume tailoring checklist per role
• Automated follow-up reminders and calendar blocks