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You will get a reusable Data Standardization Engine for CRM, APIs & CSV
Project details
I build reusable, production-ready Python Data Standardization Engines that automatically validate, normalize, and transform inconsistent data from CRMs, APIs, CSV, Excel, and other sources into a clean, reliable schema. The solution includes schema validation using Pydantic or the most appropriate validation framework for your data volume, source, and architecture, automatic error quarantine, detailed logging, and a modular, scalable architecture designed for ETL pipelines, analytics platforms, and data warehouses. Eliminate manual data cleanup, improve data quality, and build a reliable foundation for scalable, production-grade data processing.
Programming Languages
PythonWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$750
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Sources Mined/Scraped | 1 | 3 | 5 |
Install Script | - | ||
Test Script | - | ||
Task Automation | - |
About Lidiya
Backend & Data Engineer
Almaty, Kazakhstan - 1:01 pm local time
Whether you need backend development, workflow automation, data processing, API integrations, or modern data pipelines, my goal is to deliver solutions that are reliable, scalable, and built for long-term use.
What I can help you with:
• Backend application development
• Data engineering and pipeline development
• Workflow orchestration and automation
• Data validation, transformation, and quality assurance
• REST API development and integrations
• Database design and data platform solutions
• Reusable internal tools, SDKs, and automation components
I design backend systems with a strong focus on clean architecture, reliability, maintainability, and clear communication throughout every project. My goal is to build solutions that are easy to operate, extend, and support as business needs evolve.
Steps for completing your project
After purchasing the project, send requirements so Lidiya can start the project.
Delivery time starts when Lidiya receives requirements from you.
Lidiya works on your project following the steps below.
Revisions may occur after the delivery date.
Data Audit & Schema Definition
I analyze your sample files or APIs, identify schema discrepancies, and define the target schema along with normalization rules.
Mapping & Engine Configuration
I configure field mapping, implement data validation models using Pydantic or suitable equivalent tools tailored to your data specifics, and set up standardization logic.