Mar 2021 – Feb 2022 · 11 mos

Jul 2019 – Mar 2021 · 1 yr 8 mos

• As a chief architect, responsible for leading the team to design and deliver end to end solutions
• FireEye’s new cloud based alert ingestion system for EX (email security) using cadence workflow
• Migration of FireEye core legacy database to AWS and integration of CyberArk as security vault for storing sensitive information
• Provide expertise in performance optimisation for FireEye Endpoint Security Platform for Incident Response
• Deliberations with PM/PO/VP to understand business requirements

Jan 2018 – Jun 2019 · 1 yr 5 mos

• Onboarding of X15 as a unified database platform for FireEye products
• Designed and implemented X15 AAA with FireEye IAM for both REST and DBC endpoints
• Initiated product enhancements, designed highly critical features and led the team members during its implementation. Includes, column-wise pagination support for wide column tables & query data response limiting feature by introducing cell level data limits and cursors to fetch data on demand
• Provided expertise in security fixes, memory corruption fixes, caching and performance optimisations
• Evaluated different CICD Frameworks (Concord, Spinnaker, JenkinsX) to deploy Data Explorer as SAAS solution
• Resolved several critical customer issue

Mar 2013 – Jan 2018 · 4 yrs 10 mos

• 🚀 Joined on Day 0 as the first engineering team member, working closely with the CTO to build the platform from the ground up. Played a key role in establishing and leading the initial India engineering team during the early years.
• Designed and implemented the distributed metadata storage layer with CRUD capabilities via REST APIs.
• Developed a Postgres-compatible JDBC server-side state machine, enabling BI tools to use X15 like a standard relational database.
• Solved paginated queries for terabytes to petabytes of data using a cursor-based approach, optimizing performance with flexible output formats like XJSON, NDJSON, and CSV.
• Created an automated code generation framework from ERM models, speeding up development by auto-generating REST APIs, JDBC interfaces, and DB access layers.
• Enabled external relational database queries and join operations with internal tables, expanding data integration for BI tools without ingesting data.
• Supported metadata import/export, facilitating workspace migration and SDLC workflows by exporting metadata as DDL.
• Implemented row- and column-level security filters, improving privacy compliance by controlling sensitive data access.
• Key contributor to X15’s in-house SQL query engine, supporting distributed machine data workloads. Contributed across SQL parsing, logical plan construction, optimizations, and query execution orchestration.
• Developed a Record & Replay framework to replicate JDBC/REST interactions, which was further extended to automate testing and improve debugging.
• Demoed the platform to potential customers, showcasing its capabilities and providing feedback to influence the product roadmap.

Jan 2013 – Jan 2015 · 2 yrs · Delhi, India

• Co-founded CAace (2012–2016), an online test prep platform for CA-CPT and later CS Foundation aspirants. Directed technical design, development, and deployment of a scalable, reliable mock testing system. Led digital marketing efforts, co-branding initiatives, and strategic partnerships with coaching institutions to expand reach and drive adoption. The platform offered a seamless test-taking experience with detailed analytics, including topic-wise proficiency and personalized improvement insights.

Apr 2012 – Mar 2013 · 11 mos · Hyderabad, Telangana, India

• 🏆 Recipient of the Informatica Spot Award
• 📌 Co-inventor of a patented algorithm for optimized data subsetting (2012)
• Led core development in the MapGeneration engine, the heart of Informatica’s Persistent Data Masking & Data Subset (PDMDS) product. This engine translated business logic into optimized PowerCenter mappings, enabling scalable, secure data subsetting.
• Co-invented a patented algorithm that transformed data subsetting into an entity graph problem, effectively handling cyclic dependencies and normalizing complex relationships.
• Applied relational algebra transformations to generate optimized execution plans, achieving a 6x improvement in accuracy and performance.
• Implemented advanced data masking scenarios, integrating seamlessly with PowerCenter for automated mapping generation.
• Collaborated with a team of 3 engineers, driving technical design and execution across development and QA.
• Recognized with the Informatica Spot Award for outstanding innovation and technical leadership.

Jul 2010 – Mar 2012 · 1 yr 8 mos · Hyderabad, Telangana, India

• Worked on Informatica’s Persistent Data Masking & Data Subset (PDMDS) product, which helps enterprises create secure, functionally intact subsets of application data for testing and analytics.
• Developed backend CRUD operations for data subset metadata entities and built corresponding UIs using RWT.
• Revamped the TDM Accelerator, introducing a graph-based data collection approach and a new interactive installer — reducing execution time from 60 minutes to 3 minutes.
• Optimized key modules for metadata import and plan generation, delivering a 5x performance boost in system throughput and responsiveness.
• Contributed to improving user experience, scalability, and overall system performance in a high-impact data privacy product.

Jan 2008 – Jan 2010 · 2 yrs

• Edge Detection Optimization in Image Processing for Robotics Applications
• 📄 Research paper published at IPCV Conference, USA (2010)
• Explored the intersection of robotics and computer vision by developing a novel heuristic-based edge detection algorithm tailored for high-performance image processing in robotic systems.
• Designed an optimized edge detection algorithm that significantly reduced computational overhead while preserving edge quality—critical for real-time robotic vision.
• Conducted extensive comparative analysis against traditional algorithms, demonstrating notable runtime improvements with comparable output accuracy.
• Results contributed to the growing need for efficient computer vision systems in robotics, paving the way for faster onboard image processing.
• Research was recognized and published at the IPCV Conference (USA, 2010).