Nagarjuna HN HN

Entry-level Software Engineer

Bengaluru 0+ yrs exp 81 · Excellent

About

Entry-level Software Engineer with hands-on experience developing full-stack web applications using JavaScript, Node.js, React.js, Express.js, MySQL, and REST APIs. Strong foundation in backend development, relational database design, authentication, authorization, and secure application development, with additional experience in data collection, data cleaning, pattern analysis, visualization, and technical reporting. Demonstrated ability to translate application and experimental data into reliable systems, dashboards, and actionable insights.

Skills & Expertise (27)

Git Intermediate

6.0/10

Years Exp

HTML5 Intermediate

6.0/10

Years Exp

CSS3 Intermediate

6.0/10

Years Exp

GitHub Intermediate

6.0/10

Years Exp

Python Intermediate

5.5/10

Years Exp

SQL Queries Intermediate

5.5/10

Years Exp

Postman Intermediate

5.5/10

Years Exp

MySql Intermediate

5.5/10

Years Exp

CRUD Operations Intermediate

5.5/10

Years Exp

REST API development Intermediate

5.5/10

Years Exp

Express.js Intermediate

5.5/10

Years Exp

Node.js Intermediate

5.5/10

Years Exp

JavaScript Intermediate

5.5/10

Years Exp

React.js Intermediate

5.5/10

Years Exp

SQL Intermediate

5.5/10

Years Exp

Nodemailer Intermediate

5.0/10

Years Exp

Microsoft Azure Fundamentals Intermediate

5.0/10

Years Exp

AWS Fundamentals Intermediate

5.0/10

Years Exp

RBAC Intermediate

5.0/10

Years Exp

Authorization Intermediate

5.0/10

Years Exp

Authentication Intermediate

5.0/10

Years Exp

BCrypt Intermediate

5.0/10

Years Exp

JWT Intermediate

5.0/10

Years Exp

Joins Intermediate

5.0/10

Years Exp

Schema Design Intermediate

5.0/10

Years Exp

Relational Database Design Intermediate

5.0/10

Years Exp

Recharts

Work Experience

Research Intern

Mother India Forming Pvt. Ltd.

Jan 2026 - Present

Collected, structured, and labelled experimental measurements including weld angles, flow-line patterns, and defect counts to prepare reliable datasets for AI model training. Analysed experimental measurements to identify defect patterns and trends, supporting quality assessment and data-driven technical evaluation. Validated data accuracy and consistency across repeated measurement cycles and organized findings into structured quality reports for internal review.