
Results-oriented IT professional with over 2 years of experience in analyzing and developing distributed web applications using Java, Python, Spring Restful Web services, Spring Boot, Hibernate, and SQL Server. Skilled in Microservices Architecture and proficient in hosting Microservices on Microsoft Azure. Extensive knowledge of Spring Boot, Spring MVC, Spring ORM, Spring Data JPA, Hibernate, Restful Web Services, JDBC, and JSP. Valuable contributor to prestigious agile projects as a System Engineer with expertise in Agile and Scrum Methodology. Possesses strong domain knowledge in Health Care and insurance projects. Experienced in working with NoSQL databases like Redis and MongoDB. Proficient in SQL Server and Informix Databases. Hands-on experience with Dynatrace and Splunk for efficient debugging and problem analysis. Solid understanding of JavaScript, HTML, CSS for front-end development. Proficient in IDEs like Eclipse and STS for web application development. Successfully deployed services in managed services cloud across various environments such as DEV, QA, and Prod. Well-versed in JSP, Servlets, JDBC, and Spring Security. Skilled in configuring and deploying applications on Apache Tomcat on the Windows platform. Adaptable to new technologies and environments with a strong ability to learn quickly. Collaborative team player with excellent communication skills who works effectively with testers and other team members to ensure software product development meets high-quality standards. Demonstrated efficiency in both independent and team work environments with a willingness to learn new concepts and embrace challenges. Detail-oriented individual with exceptional technical troubleshooting and problem-solving abilities.
Project Title: REST API Scraper & Data Aggregator with Python
Overview:
Developed a Python-based data scraper to extract and process structured data from public REST APIs. The project focuses on automating data collection, cleaning, and storage for further analysis.
Key Features:
API Integration: Used Python's requests library to interact with a RESTful API (, CoinGecko).
Pagination & Rate Limiting: Handled paginated responses and respected API rate limits using backoff strategies.
Data Processing: Cleaned and normalized JSON responses into tabular formats using pandas.
Scheduling: Implemented periodic data pulls using schedule and cron jobs.
Data Storage: Stored processed data in CSV format and
into /
PostgreSQL using SQLAlchemy.
Error Handling: Built-in retry logic and exception handling for network/API failures.
Technologies: Python, REST API, requests, pandas, SQLAlchemy, PostgreSQL, schedule, logging
Sample Output: Collected and stored daily cryptocurrency price data for top 100 coins with timestamps, percent changes, and volumes.
Java
C language
DotNet
SQL
HQL
Hibernate
MySql