Aug 2022 – Aug 2025 · 3 yrs · Bengaluru, Karnataka, India

• Developed terabyte-scale Apache Spark data pipelines in Oracle Cloud Infrastructure(OCI) for ingesting and aggregating real-time global customer usage data. Designed a scalable, fault-tolerant architecture processing billions of records daily, providing actionable insights through real-time reporting.
• Engineered an enterprise-wide Generative AI RAG chatbot utilizing a vector database for high-speed
• document retrieval and fine-tuned LLMs for precise, context-aware query responses. Streamlined internal operations by automating 60% of manual query handling, improving query resolution accuracy by 30%, and boosting cross-departmental efficiency.
• Redesigned data load processes by migrating from a legacy relational data warehouse to the Delta Lake ecosystem, leveraging ACID compliance, dynamic schema evolution, and time travel to ensure superior data integrity and auditability. Optimized storage with file compaction and partitioning, reducing I/O overhead and boosting query performance by 40%, while seamlessly integrating with Spark-based ETL workflows for real-time analytics and cost-efficient data management.
• Developed an Instance and Rack Decommissioning Dashboard that accelerated throughput for decommissioning bare-metal and virtual machine instances. Enhanced multi-dimensional visibility (rack, host, and instance levels), optimising data center resource allocation and saving thousands of dollars annually by improving operational efficiency and reducing idle resource costs.
• Implemented Data Archival and Purging Frameworks: Led the design and implementation of robust data archival and purging systems, automating the identification of cold and inactive data. Migrated historical data to cost-effective, long-term storage while purging obsolete records in compliance with retention policies. Achieved a 25% reduction in long-term storage costs and enhanced overall database performance by optimizing active data sets.

May 2021 – Aug 2021 · 3 mos · Bengaluru

• Pioneered research in object segmentation by leveraging airborne and spaceborne LiDAR, driving a notable increase in segmentation accuracy and advancing precision in geospatial analysis for forestry applications.
• Engineered an innovative tree segmentation model utilizing a hybrid machine learning and signal processing framework, achieving an 18% boost in model accuracy, thereby setting a new benchmark for high-precision environmental monitoring systems.
• Implemented cutting-edge data fusion techniques, seamlessly integrating geospatial point cloud data
• with hyperspectral imagery to significantly enhance classification models, leading to more refined and actionable environmental insights.

Jun 2019 – Aug 2019 · 2 mos

• Conducted penetration testing on web applications and IP addresses, identifying vulnerabilities such as SQL injection, XSS, and privilege escalation using tools like Burp Suite, Nmap, and Metasploit.
• Prepared detailed vulnerability reports, outlining security risks, impact analysis, and remediation strategies for both technical teams and executives.
• Assisted in red team exercises, simulating real-world cyber threats using phishing, privilege escalation, and lateral movement to enhance security defenses.
• Collaborated with security teams to strengthen network security, enhance access controls, and improve incident response strategies.