🧠 Insight Report

This analysis was automatically generated based on your selected filters (or full dataset). It offers a clear view of salary and role trends in tech jobs between 2020–2023, sourced from a public Kaggle dataset. The goal: demonstrate full stack backend capability and data informed reasoning.

📊 Key Metrics

• Total roles analyzed: 2,584
• Average salary: $133,409
• Median salary: $130,000
• Most common role: Data Engineer
• Remote heavy jobs (50%+): 54.1%

📈 Year on Year Salary Growth

• 2021: +$283 compared to previous year
• 2022: +$36,539 compared to previous year
• 2023: +$16,821 compared to previous year

🔍 Analytical Observations

• Steady salary growth, especially post-2021, aligning with increased tech investment post-COVID.
• Dominant roles like Data Engineer reflect market demand for data infrastructure and backend skills.
• ~54.1% remote shows trust in distributed teamsstrong signal for automation and asynchronous delivery.
• Salary variance is not linear impacted by company size, region and experience level.

🧠 Strategic Interpretation

The insight here isn't just about pay, it's about correlation: remote flexibility, title inflation, career progression and backend trust all show in numbers.

As a backend engineer, I interpret this data with architecture and delivery in mind. CI/CD readiness, secure APIs, scalable teams, those are the deeper patterns behind these roles.

🚀 Why It Matters

Anyone can scrape data, but to turn it into understanding, that’s what makes a difference. This project isn’t just about charts. It’s about turning raw tech salary data into business insight and engineering strategy.

Report generated with Python + Django. Dataset sourced from Kaggle. Designed to simulate decision making insights and demonstrate backend + data capability in hiring scenarios.