Building a production MRR pipeline in dbt: the modelling decisions that made it work

Modelling MRR and the design decisions taken.

Orchestrating dbt Pipelines with Apache Airflow

Automated an end-to-end SaaS data pipeline with daily data generation, dbt model runs, and validation tests using Airflow DAGs. Deployed via Docker Compose with environment-based credential management.

SaaS MRR Modelling with dbt & BigQuery

Built a dbt pipeline transforming raw subscription and payment data into Gross, Net, and Collected MRR for a multi-product SaaS business handling monthly/yearly billing, cancellations, plan changes, and failed payment retries.

Synthetic SaaS Billing Dataset

Built a Python pipeline that simulates a realistic SaaS billing system, generating linked data across subscriptions, invoices, payments, and discounts which loads incrementally into BigQuery. Designed to support MRR modeling, churn analysis, and revenue reporting.

Efficient Reddit ETL: Scraping, Cleaning, and Cloud Hosting

Explore Reddit Data: the project dives into web scraping, Excel cleaning, and PySpark analysis. Learn to host processed data on AWS S3 for seamless insights. Perfect for anyone keen on practical web data handling and analysis!

Mastering SQL Window Functions

Exploring real world problems for advanced data insights with SQL queries using powerful window functions.

SQL Vault

A curated collection of SQL questions and solutions, demonstrating my expertise in designing efficient database structures, writing complex queries, and addressing real-world data challenges in different SQL environments.

Statistical Data Analysis - Analyzing Customer Behavior Patterns

Examining buying habits by gender, age, and marital status through visuals and stats to reveal insights. This analysis helps businesses make better decisions and improve marketing strategies.

R Shiny Dashboard

Beer reviews is a data visualization application that shows ratings of over 18000 beers. Created using R environment and hosted on R shiny apps.

Data Transformation

Transforming json file into three different .csv files using python pandas.