About

Focused on reliable, readable data systems

I am focused on data engineering fundamentals: designing ETL/ELT pipelines, writing clear SQL, modeling data for analytics, and building reproducible systems. I enjoy projects that involve messy raw data, transformation logic, orchestration, and making data trustworthy.

How I present engineering work

I describe projects through the data flow: sources, ingestion, staging, transformations, models, checks, and outputs. This keeps the portfolio focused on engineering decisions instead of vague tool lists.

Resume highlights

  • Built batch ETL pipelines using Python and SQL.
  • Designed staging, dimension, fact, and mart tables.
  • Used orchestration tools to schedule and monitor workflows.
  • Added data quality checks to improve trust in output datasets.
  • Containerized projects with Docker for reproducibility.

Skill groups

Languages

Python, SQL, Java, C++

Databases / Warehouses

PostgreSQL, BigQuery, Snowflake

Data Engineering

ETL/ELT, Batch pipelines, Data modeling, Data quality checks, Data validation, Workflow orchestration

Tools

dbt, Airflow, Docker, Git, Linux, Vercel

Cloud

AWS, GCP