I will build an etl data pipeline with python mysql and power bi
Data Engineer
About this Gig
Are you struggling to move, transform, or load your data reliably?
I build production-ready ETL (Extract, Transform, Load) data pipelines using Python, MySQL/PostgreSQL, and Power BI giving you clean, structured, and automated data workflows from source to dashboard.
What I deliver:
- Custom Python ETL scripts that extract data from your source systems (databases, APIs, CSV files)
- Data transformation with cleaning, validation, and business logic applied
- Loading into MySQL or PostgreSQL using a star schema data warehouse design
- Power BI dashboards connected to your transformed data
- Full documentation and a clean GitHub repository
Tech stack I use:
- Python (pandas, SQLAlchemy, psycopg2)
- MySQL / PostgreSQL
- Power BI
- GitHub Actions for CI/CD and scheduled pipeline runs
- Apache Airflow / cron orchestration (Standard and Premium packages)
Why choose me?
I have built a complete food order ETL pipeline as a portfolio project handling real-world challenges like null values, schema conflicts, and incremental loading. I write clean, unit-tested, well-documented code you can confidently hand off to your team.
What I need from you:
Details about your data source, target database, and reporting goals
Destination Platform:
PostgreSQL
•
MySQL
Tools & Platforms:
Other
My Portfolio
FAQ
What data sources can you connect to?
I can connect to MySQL, PostgreSQL, CSV/Excel files, REST APIs, and Google Sheets. If you have a different source, let me know and I will assess feasibility before we start.
Do I need to provide sample data before ordering?
Yes, sharing a sample of your source data (even 10-20 rows) helps me understand your schema and build a more accurate pipeline. A sanitized sample with no real personal data is fine.
Will I receive the Python code and documentation?
Yes. All packages include the Python ETL scripts and a GitHub repository link. Standard and Premium also include full technical documentation covering setup, configuration, and how to run or schedule the pipeline.

