Greater Boston
Software engineer and open source contributor. Especially interested in software infrastructure, distributed systems, and open source software. Currently working on the Python Database Experience team at MongoDB.
I work on PyMongo, the open source Python library for MongoDB with tens of millions of monthly downloads, and its associated open source libraries: MongoDB Django Backend, PyMongoArrow, langchain-mongodb, and others. Nearly all of my work is publicly viewable on my Github profile. - Created native asynchronous API for the MongoDB Python library, improving highly-concurrent performance dramatically - Wrote the specification for Object-Document Mapper (ODM) performance testing across all MongoDB ODMs to catch regressions and concretely measure optimization improvements - Streamlined disparate database transaction APIs using Python context managers, reducing usage errors and encouraging correct patterns in user code - Achieved a significant speedup of CPU-bound translation between native Python objects and binary representations by optimizing Python/C extension module - Significantly reduced client error rates and increased throughput during database overload by leading development of a distributed backpressure system across all MongoDB language library teams to intelligently backoff when needed - Added standardized debug logging, allowing users to provide detailed tracebacks and error details in bug reports and support requests
The Data Analytics team builds large-scale data pipelines and platforms to process and provide access to over 300TB of data from over 2 billion devices daily. I was one of two engineers responsible for the critical ETL pipeline and dependent services that form the core of the team’s mission. - Reduced the latency of critical data collection by 75%, allowing end users to gain insights and deploy fixes quickly. - Led creation of end-to-end testing across several critical projects, reducing user reports by double-digits and saving hundreds of engineer hours yearly. - Developed Scala data enrichment framework, allowing developers to efficiently create custom data processing and standardize feature architecture and testing - Added real-time de-duplication to Samza ETL pipeline processing over 300TB of data daily, saving dozens of engineer hours monthly
• Built Spring + Kafka dispatcher-worker service to compress, encrypt, and upload terabytes of telemetry and analytics data from HDFS to S3, unifying data delivery to external teams • Implemented secure Postgres database layer and Java library to handle real-time request and upload progress, key management, and encryption, minimizing developer overhead • Created authenticated Spring REST API to provide hundreds of teams with self-service access to critical data and automated job integration, saving thousands of developer hours • Wrote React + Typescript web UI for API, allowing users to view request progress, get encryption keys, and download S3 files without detailed technical knowledge
Built several new features for open-source interactive computing and analysis software with millions of users in data science, academia, and technology. Worked in a largely independent team of one other software intern and a UX/UI designer intern, with collaboration and mentoring from core open-source contributors. Created our projects with modern technologies like IPython, React, Python, and asynchronous Typescript. At the end of the summer, we presented our projects at JupyterCon, with over 800 professionals and academics attending. In total, our projects collectively received over 8,000 downloads over the course of the summer. • Built keyboard shortcut editor with asynchronous React + Typescript frontend, significantly improving user workflow and productivity • Overhauled integrated Git extension built with React, Typescript, and Python, completely rewriting the existing codebase and giving users effective access to version control as well as providing an accessible way to learn Git • Created Plyto, a machine learning and data science visualization toolkit for Python that uses a custom-built framework and API