About Me

I’m a Data Engineer with hands-on experience building scalable data pipelines and automation workflows in production environments.

I currently work at Whimstay, designing and maintaining ETL pipelines that ingest data from dozens of external sources, transform it reliably, and make it analytics-ready for business and product teams.

Professional Experience

Data Engineer / Data Analyst — Whimstay

2024 – Present

Designed and implemented ETL pipelines extracting booking and pricing data from 70+ external websites using web scraping and API integrations.
Led a small team to build automated data ingestion systems deployed on GCP Cloud Run using Python, Docker, and Git.
Automated validation of 300K+ URLs powering competitive pricing comparisons displayed directly to end users.
Built data cleaning workflows processing ~29K U.S. geographic polygons, improving accuracy of location-based data.
Wrote optimized SQL queries in BigQuery to support company-wide dashboards and reporting.
Queried MongoDB and PostgreSQL production databases to extract, validate, and reconcile datasets.
Developed an asynchronous scraping system with proxy rotation to collect guest reviews from 50K+ properties, continuously updating production data.

Side Projects

Excel Report Automation with Python

Built Python-based automation scripts to generate and maintain Excel reports, reducing manual effort and improving reliability.

View on GitHub

Crypto Data ELT Pipeline

Designed and implemented an ELT pipeline to collect, transform, and load cryptocurrency market data from multiple APIs into BigQuery for analysis and visualization.

View on GitHub

What I Work With

Python (Pandas, NumPy, Matplotlib, GeoPandas)
SQL & Data Modeling
BigQuery, PostgreSQL, MongoDB
GCP (Cloud Run, Cloud Storage, Cloud Scheduler)
Docker, Linux, Git
Power BI & Analytics
ETL / ELT Pipelines & Automation

What I’m Looking For

I’m seeking Data Engineer roles where I can build reliable, scalable data pipelines, work with cloud-native architectures, and collaborate closely with analytics, product, and engineering teams.