Oct 2025 – Dec 2025 · 2 mos · Bengaluru, Karnataka, India · On-site

• Designed and implemented a fault-tolerant ingestion layer that converts asynchronous Kafka consumer JSON events into Parquet format and uploads them to AWS S3.
• Developed a scheduled cron workflow to ensure reliable and timely data delivery to S3.
• Engineered an automated reporting service that reads Parquet files from S3, generates optimized CSV reports, uploads them to Google Drive, and dispatches them to end users via email.

Aug 2023 – Oct 2025 · 2 yrs 2 mos · Bengaluru, Karnataka, India · Hybrid

• Developed an editable data list gadget, allowing users to perform CRUD operations directly from the UI, seamlessly updating the database without requiring backend intervention.
• Designed and implemented RESTful APIs to handle data manipulation efficiently across multiple database systems, including PostgreSQL, Oracle, and Couchbase.
• Optimized Presto database performance by restructuring queries to consolidate multiple related requests into a single prepared statement with dynamic joins—improving system reliability, reducing latency, preventing crashes, and contributing to scalable and efficient backend system design.
• Implemented data interpolation and clustering mechanisms to enhance chart visualization, effectively filling missing data points and dynamically grouping raw data into meaningful clusters based on configurable parameters for better insights.
• Developed an on-resume and on-suspend caching mechanism to preserve gadget states, reducing redundant database queries and enhancing dashboard performance by 80%.

Aug 2022 – Jul 2023 · 11 mos · Bengaluru, Karnataka, India · Hybrid

• Built a static report generation system for dynamic dashboards, preserving interactive elements like filters, charts, infographics, maps, and more to ensure accurate and consistent data representation.
• Improved dashboard load time and responsiveness by 50% by introducing intelligent checks to avoid redundant queries for hidden or inactive components.
• Developed an offline state management feature, ensuring dashboards retain their state when transitioning from online to offline mode, enhancing user experience and reliability.
• Enhanced and modularized dynamic data processing components including forms, data lists, and charts, boosting overall system scalability, maintainability, and usability.

Jan 2022 – Aug 2022 · 7 mos

• Developed ML and DL applications tailored to client requirements.
• Researched and implemented ML and DL models based on research papers and optimized performance for real-world applications.
• Analyzed and enhanced data science prototypes, refining models and improving their accuracy and efficiency.