Software Engineer | 3+ years of experience | Java-SpringBoot, REST-API, Azure, SQL

I have 3+ years of experience in Java development, deeply involved in every aspect of the development life cycle, from conceptualisation and design to implementation, testing, and deployment.

Below are some of the key aspects of my experience:

• Java Development & Microservices: Expertise in building scalable microservices deployed on Kubernetes.
• Tools & Technologies: Proficient in Maven, Jenkins, Docker, GitHub, Postman, and various Azure services such as Databricks, Service Bus, Azure Functions, Azure Storage.
• API Development: Designed and implemented various REST APIs, processing around 10 million records each day.
• CI/CD & Automation: Streamlined deployment processes and implemented CI/CD workflows.
• Leadership & Mentoring: Actively serve as Scrum Master for the team and mentor new joiners, helping them onboard and integrate into the team efficiently.
• Problem-Solving: Strong analytical and problem-solving skills, ensuring efficient and reliable solutions.
• Spearheaded performance optimizations and architectural improvements to enhance system scalability and reliability under high-volume transactional loads.

Below are some of the accomplishments in my current role:

• Orchestrated a critical database migration from EnterpriseDB to Azure Flexible Server, refactoring multiple Java services to ensure zero-downtime and seamless data integration. Also, developed a custom data-comparison tool to validate the database migration, guaranteeing 100% data integrity post-transition.
• Involved the analysis and optimisation of an existing API to bolster application performance. Through strategic refactoring efforts, I successfully slashed the API's response render time from 24 seconds to a mere 7 seconds, thereby significantly enhancing user experience and system efficiency.
• Enhanced user experience (UX) by developing a responsive UI with dynamic CSS, allowing elements to auto-adjust to varying screen resolutions and maximize available space.
• Reduced memory consumption of a critical microservice by 20-30% under a 1 million record load by refactoring and optimizing code, eliminating previous memory exhaustion issues.
• Accelerated data processing by enhancing an Apache Pulsar message queue, increasing the consumer throughput rate by 16x while maintaining a stable publishing rate.