Java backend developer based in Kendrapara, Odisha, building scalable REST services with Spring Boot, Hibernate/JPA and MySQL. Comfortable moving up the stack into React when a project needs a full end-to-end owner. Currently deep in enterprise-grade e-commerce architecture — auth, catalog, cart, orders and payments — secured with OAuth2 and JWT.
Also works as a motivated data analyst, exploring datasets, identifying trends, and presenting findings through clear visuals using Python, SQL and Excel to support data-driven decisions.
github.com/3dharmadev | 3dharmadev.github.io | satapathy20001@gmail.com | +91-8249084184
| Type | Date | Source | Description |
|---|---|---|---|
| ⓘ Info | 2022–2023 | Masai School, Bengaluru | Java Backend Development (Full Time) |
| ⓘ Info | 2021–2022 | Lovely Professional University, Phagwara | Master of Computer Application |
| ⓘ Info | 2018–2021 | Institute of Professional Studies And Research, Cuttack | Bachelor of Computer Application |
Opens your mail client, addressed to satapathy20001@gmail.com
Debabrata Satapathy — Java Backend Developer & Aspiring Data Analyst
Full resumes, projects and links live on GitHub and the portfolio site.
Collaborative Java backend project built by five contributors in four days, modeled on an online sweet-shop ordering flow. Owned the Admin, OrderBill and SweetOrder modules covering CRUD, exception handling and user/admin backend connectivity.
Individual full-stack HR management system built in three days. Admins assign projects to departments; employees update project status, request leave, and manage their accounts.
Backend system for logging, tracking and resolving complaints through defined status stages, with role-based access for admins and users.
E-commerce clone covering product listing, cart and checkout flows — an early pass at the storefront patterns later formalized in the enterprise Spring Boot commerce architecture.
Time-tracking app clone with project timers, reporting views and a live demo walkthrough.
Analyzed the Heart Disease UCI dataset (303 records, 14 features) to identify key cardiovascular risk factors through end-to-end EDA — data cleaning, outlier detection, and feature exploration.
Built correlation heatmaps, pair plots, histograms and box plots to visualize relationships between variables and disease presence; identified age, max heart rate, and ST depression as key indicators.
GeeksforGeeks Data Science assignment. Analyzed GDP data across multiple countries and time periods; cleaned raw data, performed time-series analysis, and compared growth trajectories of developing vs. developed economies.
Created line charts and bar graphs to communicate economic patterns, drawing data-backed conclusions on GDP correlation with key economic indicators.
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