Santosh Kumar Gond

Full Stack Engineer

Noida, Uttar Pradesh, India4 yrs 5 mos experience

Key Highlights

Expert in Django and Python for full-stack development.
Automated financial workflows, enhancing efficiency significantly.
Developed algo-trading strategies for stock market applications.

Stackforce AI infers this person is a Full-Stack Developer with a focus on Fintech solutions.

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Skills

Core Skills

DjangoFull-stack DevelopmentPython

Other Skills

AJAXBootstrap (Framework)C (Programming Language)C++Cascading Style Sheets (CSS)Celery beatCore JavaData AnalysisData StructuresDjango ChannelsDjango REST FrameworkHTMLJavaSciptMicrosoft ExcelMySQL

About

Working as a full stack developer at Aptara (skills using: Python, Django, Django Channels, Websocket), worked as Python Developer at Infyni (skills used: Python, Django, Django REST Framework, Celery), Algo-Trading Developer internship at Pace Stock Broking Services Pvt. Ltd. (skills used: Python, Pandas), worked as Analyst at TransUnion Global Technology Center Pune, skilled in Django, Python, C++, Java, OOPs, Data Structures.

Experience

4 yrs 5 mos

Total Experience

10 mos

Average Tenure

1 yr 2 mos

Current Experience

Aptara

Full Stack Developer

Apr 2025 – Present · 1 yr 2 mos · Noida, Uttar Pradesh, India · Hybrid

Working here as a Full Stack Developer

DjangoFull-Stack DevelopmentDjango ChannelsPostgreSQL

Infyni

Python Developer

Jan 2024 – Feb 2025 · 1 yr 1 mo · Gurugram, Haryana, India · On-site

Student Payment Flow:
Implemented a cron job and periodic task to automatically calculate student payment amounts for the
previous month based on completed or paid canceled sessions for monthly courses.
Optimized payment workflow and reduced manual processing time from 5 days to 15 minutes,
significantly enhancing efficiency and accuracy in financial operations.
Automation of Instructor Invoice:
Automated the instructor invoice generation process using Celery Beat periodic tasks, eliminating the need for manual effort.
Optimized the invoicing workflow, reducing processing time from 3 days to just 10 minutes for
approximately 350 courses, significantly improving efficiency.