Enterprise Retail Platform

A scalable in-shop retail assistance platform built for major retail brands to manage customer engagement, promotional campaigns, offer redemption and store-level performance reporting.

The platform supported brand-specific workflows across more than 500 stores, handling high-volume customer and campaign data. It provided operational tools, dashboards and scheduled reports for retail teams.

I worked across backend development, frontend integration, automation and cloud deployment while also taking technical-lead responsibilities for one major client implementation.

My responsibilities included:

Designing and developing REST APIs using Python and Flask

Integrating APIs with React-based interfaces

Designing database tables, relationships and data workflows

Building campaign, redemption and store-performance dashboards

Creating automation scripts for reports, emails and data processing

Configuring and maintaining AWS deployment environments

Supporting production releases and resolving application issues

Coordinating junior developers and mentoring interns

Participating in client discussions, technical planning and delivery

The backend was developed using Python and Flask, with PostgreSQL and MySQL supporting transactional and reporting workloads. React and Chart.js were used for operational interfaces and analytics dashboards.

The application was deployed on AWS using EC2, S3, RDS and IAM. Production configuration included Linux, Nginx, Gunicorn, environment management, SSL, DNS configuration and basic deployment automation.

Scheduled Python jobs handled recurring reports, campaign-data processing, email delivery, file movement and database maintenance.

Supported workflows across 500+ retail stores

Processed databases containing millions of records

Delivered APIs for campaign, customer, offer and reporting workflows

Supported high-volume daily platform usage

Automated repetitive reporting and operational processes

Reduced approximately 2–3 hours of recurring manual effort per day

Adapted workflows and interfaces for multiple retail brands

Python, Flask, React.js, PostgreSQL, MySQL, AWS EC2, AWS S3, AWS RDS, IAM, Nginx, Gunicorn, Linux, Chart.js and Git.