I will build an automated etl data pipeline using python and airflow
Junior Data Scientist, ML Engineer, Python, ETL Pipelines
Over deze dienst
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.
Bestemmingsplatform:
PostgreSQL
•
MySQL
Tools & platforms:
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Mijn portfolio
Veelgestelde vragen
What data sources can you connect to?
Currently REST APIs. If you have a different source such as CSV files or a database, message me first and we can discuss feasibility.
Do I need Apache Airflow already installed?
No. I will set up the pipeline environment for you, including Docker configuration if needed.
Will the pipeline run automatically without me doing anything?
Yes. The Standard and Premium packages include fully scheduled automation using Apache Airflow that runs on your defined schedule without any manual triggering.
Will I receive the source code?
Yes, all packages include the full Python source code and DAG files.
Can you work with my existing database?
Yes, as long as you can provide connection credentials securely. I recommend discussing this before ordering.

