SMTS @ Oracle India

Bengaluru, Karnataka, India

Bengaluru

Mangaluru, Karnataka, India

Mangaluru, Karnataka, India



Bachelor's degree, Electronics and Communications Engineering
National Institute of Technology Karnataka
Intermediate, Junior High/Intermediate/Middle School Education and Teaching
Narayana Junior College - India
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I am a software engineer working at Oracle India
Andhra Pradesh
codex
gemini
Senior Member of Technical Staff at Oracle, Oct 2025 - Present · 1 yr, Bengaluru, Karnataka, India, Database multicloud Currently working on various multicloud dataplane integration features
Member Of Technical Staff at Oracle, Jun 2022 - Oct 2025 · 3 yrs 5 mos, Bengaluru, RMAN (Recovery Manager) – Core Database Engineering * Refactored legacy RMAN logging into the Attention Logs framework, designing a robust trace classification mechanism that significantly improved traceability and debugging efficiency. * Enhanced RMAN in-memory tracing by introducing conditional auto-purging, dynamic enable/disable controls, and richer diagnostic context, reducing operational overhead. Database Multicloud * Led delivery of multiple high-impact platform capabilities for ODB@Azure, including OL8 and Oracle Database 23c support, Single Node Exadata VM Clusters, custom SCAN listener ports, local file system resize, and X11M infrastructure provisioning, expanding deployment flexibility and accelerating customer adoption. * Designed and implemented core control-plane workflows and UI enhancements for next-generation Exadata services, including ExaDB-XS lifecycle management (create/remove workflows for Exascale storage vaults and VM clusters). * Designed and implemented multicloud identity and token exchange enabling Oracle Exadata Database workloads to securely access GCP, and AWS services using federated, keyless authentication (token exchange, workload identity, resource principals).
Research Internship at National Institute of Technology Karnataka, May 2021 - Jul 2021 · 3 mos, Mangaluru, Karnataka, India, • Aimed at developing a lightweight and efficient model for Retinal vessel segmentation • Developed a deep learning model based on U-net using keras • Augmented the data into random patches containing a threshold limit percent of blood vessels • Achieved over 97 % accuracy with just around 0.4 million trainable parameters • Accepted for IEEE indicon 2021 conference
Executive Member at ISTE NITK, Sep 2019 - Apr 2022 · 2 yrs 8 mos, Mangaluru, Karnataka, India
Bachelor's degree, Electronics and Communications Engineering, National Institute of Technology Karnataka
Intermediate, Junior High/Intermediate/Middle School Education and Teaching, Narayana Junior College - India