You will get Data Cleaning & Automation Specialist (Python, Excel, ETL)


Project details
A fully documented ETL pipeline that cleans, normalizes, and standardizes real‑world name data.
Each image demonstrates the process — from raw input to clean output — using regex automation, prefix/suffix removal, and casing normalization.
Built for analytics, automation, and database workflows.
Each image demonstrates the process — from raw input to clean output — using regex automation, prefix/suffix removal, and casing normalization.
Built for analytics, automation, and database workflows.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$15
|
Standard
$35
|
Advanced
$75
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | Unlimited |
Number of Pages Mined/Scraped | 1 | 3 | 5 |
Number of Sources Mined/Scraped | 1 | 2 | 3 |
Frequently asked questions
About Faiz
Data Cleaning , Automation Specialist , Regex Python and ETL
Woodbridge Township, United States - 6:04 pm local time
Specializatons : Data caleaning and formatting
File processing(CSV, Excel, JSON)
Python automation scripts
ETL style data transformations
Removing duplicates, fixing inconsistencies, validating data
Preparing datasets for dashboards, reports, or analysis
Tools & Technologies
Python, pandas , CSV/Excel handling, JSON parsing,automation logic,loops,functions , data validation.
strengths :
Clean , readable code
Fast turnaround
Clear communication
Reliable and detail oriented
Focused on accuracy and consistency
Ready to help you clean your data or automate your workflow - message me to get started.
Steps for completing your project
After purchasing the project, send requirements so Faiz can start the project.
Delivery time starts when Faiz receives requirements from you.
Faiz works on your project following the steps below.
Revisions may occur after the delivery date.
Run the ETL Cleaning Pipeline
Your data is processed through my automated Name Cleaning ETL Pipeline, which includes: Normalization Prefix/Suffix removal Casing fixes Comma/reversed name correction Whitespace cleanup Apostrophe/hyphen standardization

