You will get custom SQL ETL pipelines and data cleaning
Project details
I build clean, optimized, and fully automated SQL ETL/ELT pipelines tailored to your exact business logic
What sets this service apart:
Production-Ready Code: Clean, well-documented, and error-handled SQL scripts that run smoothly without breaking.
Smart Engineering: Focus on performance optimization (CTEs, Window Functions, and Indexing) to save cloud database compute costs.
End-to-End Reliability: From raw data cleaning to final Data Warehouse loading and automated scheduling, you get a fully functional, scalable solution ready for analytics.
What sets this service apart:
Production-Ready Code: Clean, well-documented, and error-handled SQL scripts that run smoothly without breaking.
Smart Engineering: Focus on performance optimization (CTEs, Window Functions, and Indexing) to save cloud database compute costs.
End-to-End Reliability: From raw data cleaning to final Data Warehouse loading and automated scheduling, you get a fully functional, scalable solution ready for analytics.
Database Type
MySQL, PostgreSQL, MongoDBWhat's included
| Service Tiers |
Starter
$10
|
Standard
$15
|
Advanced
$25
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Queries | 5 | 10 | 15 |
Query Debugging | |||
Query Optimization | - | ||
Query Scheduling | - | - | |
Query Analysis | - | - | |
Source Code | - | - |
About Fady
Data Engineer | Cloud Data Warehousing & ETL/ELT Pipelines
Alexandria, Egypt - 9:29 am local time
Third-year Data Science student at Alexandria University with a genuine passion for data engineering. I am still early in my
learning journey, building my skills in Python, SQL, and cloud platforms through university courses and self-driven projects. I
am looking for an internship where I can learn from experienced professionals, gain real-world exposure to data pipelines and
infrastructure, and grow into a strong data engineer.
Projects
E-Commerce Customer Segmentation Project - Python, pandas, NumPy, matplotlib, seaborn, Sklenar 5/2026
* Developed an automated end-to-end data pipeline to programmatically fetch, extract, and clean a high-volume online retail
dataset using the Kaggle API and Pandas.
* * Engineered robust exploratory data analysis (EDA) scripts to handle missing values, filter time-series trends, and isolate
spatial anomalies across transactional features.
Steps for completing your project
After purchasing the project, send requirements so Fady can start the project.
Delivery time starts when Fady receives requirements from you.
Fady works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements Gathering & Data Assessment
I review your data sources, schemas, and requirements to understand the target output and business logic needed for the pipeline
Data Cleaning & Transformation Design
I write optimized SQL scripts to clean, structure, deduplicate, and transform your raw data according to your business rules