[email protected] ****| +1 (518) 776-0449 | Github | LinkedIn **| New York, U.S.

Experiences

Software Engineer

OnePay (Apr 2025)

• Maintained and scaled core services platform (TBA).

Software Engineer (Vice President), Technical Lead

Goldman Sachs (GS), Legend - Core Data Platform (Mar 2019 - Mar 2025)

• Developed and scaled Legend data platform (~15K MAU, ~1.5K QPS, serving 90% OLAP use cases at GS):
  • Modularized and scaled the platform by enabling support for plugins maintained by external contributors (serving 60+ plugins).
  • Maintained Pure—Legend’s logical modeling language, including its grammar, parser, compiler, and text-based IDE (~7K MAU).
  • Built dev-tools, set up end-to-end testing, CI/CD pipeline, showcase, and documentation framework to scale development.
  • Established design systems and created application framework to fast track development of 6+ new web-applications in the platform.
  • Re-architected connection pool manager to better streamline support for various authentication/authorization mechanisms (Kerberos, Ping, OAuth, Identity Federation, etc.) to unlock new L0, L1 data warehouse use cases.
• Led team of 5+ engineers working on major entry-point applications of Legend ecosystem, leading to 5 successful product launches (serving ~10-12K MAU):
  • Legend DataCube (~1K MAU): prototype launched in July 2024, aimed to capture internal market of 15-20K MAU by offering a more streamlined and business-friendly grid-centric EDA power-tool for strategists and traders.
  • Legend DataSpace (~2K MAU): launched internally in April 2023 to power firm-wide data curation, accelerating onboarding and cross-team collaborations with taxonomy-based data search and navigation with enriched metadata (associated datasets, models, contracts, lineage, etc.).
  • Legend Query (~8K MAU and ~3K monthly published queries): launched in June 2022 to migrate and absorb a legacy ad-hoc data-exploration tool by offering a model-first approach that integrates more seamlessly with Legend platform to build, share, and productionize data queries.
  • Legend Studio (~3K MAU): launched in June 2019 and has since become the firm’s primary tool for data modelers. With an ergonomic form-based modeling workflow backed by a solid SDLC framework, Studio has transformed the data-modeling experience at GS by decentralizing and redistributing the legacy monolithic graph of ~7M data model objects to improve project load time by ~20x (saving ~50K dev hours per month).
  • Legend Services (~3K MAU): launched internally in January 2019 to serve as the core query execution and monitoring platform, which powered major data refiner pipelines, critical auditing, and reporting functions at GS (currently processing ~1.2K QPS).
• Drove the open-sourcing of 6+ projects in Legend stack (since Fall 2020). Maintained and grew the community around these projects:
  • Externalized the codebases, document contribution guidelines, development processes, and designed homepage for Legend.
  • Optimized CI/CD pipelines for build, test, release, and code-quality checks to boost development productivity and reduce operational costs (saving ~10K build hours per month).
  • Created and maintained Legend Omnibus, a zero-config Docker-based **deployment of the Legend stack that simplified and accelerated the onboarding process and has become the de-facto standard to deploy Legend externally, particularly in public demos, conferences, and workshops (e.g. Snowflake Summit 2023, Grace Hopper Celebration 2023, OSSF 2023) (~5.3K downloads).

Software Engineer

Goldman Sachs (GS), QuBITS - Data Model Engineering (Jul 2018 - Mar 2019)

Maintained the most popular text-based search tool at GS (~7K MAU) that streamlined and fast tracked creation of interactive grid view and visualization dashboard for Elasticsearch databases (serving 11K+ dashboards, saved ~1.1M dev hours).

Software Engineer Intern

Goldman Sachs (GS), Business Intelligence Platform (Summer 2017)

• Improved SDLC workflow around reviewing and productionizing analytics dashboard built with Tableau and Qlik Sense.
• Scaled the system to support more BI products.

Presentations