RAWG Gaming Insights

An end-to-end data engineering project built around the RAWG API to analyze gaming trends and ratings.

Highlights

1. Automated ingestion of 40K+ game records from RAWG API into Amazon S3 with boto3.

2. Transformed and normalized JSON data using Databricks (PySpark), cutting query latency in AWS RDS (PostgreSQL) by 40%.

3. Designed a normalized data warehouse for structured analytics.

4. Built interactive dashboards in Google Looker Studio, reducing manual analysis time by 50%.

5. Orchestrated workflows with Databricks Jobs and maintained version control with Git.

Tech Stack

• Python
• boto3
• Databricks
• PySpark
• Amazon S3
• AWS RDS (PostgreSQL)
• Google Looker Studio
• Git