I will build an automated etl data pipeline using python and airflow

Is your data sitting in APIs or files with no automated way to collect and store it? I build production-ready ETL pipelines using Apache Airflow 3 and Python that extract, transform, and load your data on a schedule, fully automated, with zero manual work.

What I deliver:

• Automated pipeline with independent extract, transform, and load tasks
• Apache Airflow 3 with TaskFlow API and daily scheduling
• Multi-container Docker stack for clean, reproducible deployment
• PostgreSQL database with structured, queryable records
• Full source code delivered via GitHub

Why me? I have a peer-reviewed IEEE conference publication, dual DataCamp certifications (Certified Data Scientist and Certified Associate Data Scientist), and a research internship with a UK-based AI lab. My ETL pipeline runs live in production, accumulating 365+ structured records per year with zero manual intervention.

I work with: REST APIs and file-based data sources, loading into PostgreSQL.

Note: Please message me before ordering to discuss your data source and requirements.