● LiveData AnalyticsPython

DAJobs

A Python-powered analytics dashboard for the Australian job market — tracking remuneration trends, role distribution, and hiring data across data analyst positions. Built to practice and demonstrate real-world data engineering skills.

AU
Australian Market
Live
Hosted on Subdomain
Python
Core Language
nginx
Reverse Proxy

What is DAJobs?

DAJobs (Data Analyst Jobs) is an analytics platform that scrapes, processes, and visualises job listing data for data analyst roles across Australia. The goal was simple: turn the noise of job boards into actionable insights — what skills are in demand, what salaries look like, where the roles are, and how the market is shifting.

It runs on a secure subdomain at dajobs.wfdnelson.com and uses Streamlit as the frontend framework — chosen for its fast iteration cycle and data-friendly component library.

Features

💰

Remuneration Tracking

Salary ranges scraped and normalised from job listings — see what data analyst roles actually pay across different seniority levels.

📊

Role Distribution Charts

Interactive charts showing job volume by category, location, and required skills. Spot what employers actually want.

🗺️

Geographic Breakdown

Where are the roles? City-level breakdown of job concentration across Australian markets.

🛠️

Skills Demand Analysis

Which tools and tech stacks keep showing up in job descriptions? Ranked by frequency across listings.

📅

Trend Tracking

Time-series data showing how the market has moved — useful for timing applications and understanding demand cycles.

🔒

Secure Subdomain

Deployed on its own subdomain behind nginx, with TLS — proper production setup, not just a dev server.

Tech Stack

PythonStreamlitpandasNumPynginxLinux VPSTLS/SSL

Data Layer

  • Python scraping pipeline for job data
  • pandas for data cleaning and analysis
  • NumPy for statistical summaries

Deployment

  • Streamlit app server
  • nginx reverse proxy with TLS
  • Hosted on Linux VPS alongside wfdnelson.com

Why I Built It

I was looking at the data analytics job market to understand what skills to prioritise — and found that job boards are noisy and inconsistent. Rather than manually scanning listings, I built a tool to do it for me.

DAJobs is a personal utility that became a portfolio piece. It demonstrates end-to-end data work: scraping, cleaning, analysis, visualisation, and deployment. The kind of pipeline a data analyst is expected to build.

Live at dajobs.wfdnelson.com