Data Engineer building reliable pipelines, data warehouses, and production-grade data systems.

I'm bvffer, a data engineer focused on building reliable pipelines and turning raw data into something teams can actually trust.

My interests span ETL/ELT pipelines, data warehousing, streaming systems, orchestration, and data infrastructure. I enjoy working across the full data lifecycle, from ingesting and modeling data to building the pipelines and platforms that keep it flowing correctly at scale.

I use GitHub as a record of my work, experimentation, and continuous improvement. The repositories below are intended to show how I approach real data engineering problems through pipeline design, data modeling, documentation, and shipped projects.

My current stack covers data pipelines, warehousing, orchestration, and the infrastructure that supports them.

Short examples of how I solve data problems for real business needs.

01 · Customer Data Processing Workflow A data workflow that cleans incoming customer files and stores them in a reliable database. View Project →

02 · Customer Data ETL Pipeline Extracts customer data from CRM and Excel sources into a unified data warehouse with Docker and CI/CD. View Project →

03 · Cryptocurrency ETL Pipeline Collects crypto market data from CoinGecko API, transforms it, and stores it as a historical dataset. View Project →

04 · Amazon Egypt Product Scraper Scrapes product data from Amazon Egypt with rate-limited HTTP fetching and structured CSV output. View Project →

05 · Weather Data Pipeline with Airflow Automated weather data pipeline using Apache Airflow for scheduled extraction, transformation, and loading. View Project →

06 · X (Twitter) Scraper & Post Analyzer Collects and analyzes posts from X with sentiment processing for trend insights. View Project →

A snapshot of my GitHub activity and data engineering work.

For opportunities, collaboration, technical discussions, or project-related questions, you can reach me through the links below.