• Built an event-driven Kafka pipeline eliminating manual entry for thousands of financial records daily, enabling real-time data synchronization across internal platforms

• Led migration of legacy batch workflows to Spring Boot microservices orchestrated with Apache Airflow, reducing manual effort in job scheduling and deployment processes by ~40%

• Designed a centralized feature flag system across backend and frontend, enabling controlled rollouts and reducing deployment risk across multiple platforms

• Supported production deployments, diagnosing CI/CD failures and resolving release issues to ensure stable production rollouts

• Migrated an ETL job from Helios to a Kubernetes (K8s) cluster, reducing manual intervention and improving reliability of data pipeline execution.

• Developed a full-stack data management tool (React + Spring Boot) used by analysts to manage financial datasets and workflows.

• Implemented Elasticsearch-based semantic and hybrid search, improving relevance and enabling efficient retrieval of structured and unstructured financial data across internal platforms.

• Worked extensively with Java, applying various data structures to solve real-world problems

• Enhanced technical skills and deepened understanding of core software engineering concepts

• Received mentorship and guidance to develop professional expertise and problem-solving abilities

• Participated in the Goldman Sachs Engineering Possibilities program, exploring career opportunities in technology within the finance sector

• Engaged in hands-on learning experiences and projects related to engineering practices and financial technology

• Developed advanced skills in algorithms, data structures, and software development

• Gained hands-on experience with real-world coding challenges and problem-solving