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I had the rare opportunity to architect Redfin's in-house E2E development tool from the ground up using Java and React.js. Engineers use it daily to build their code on VMs, run recommended tests, initiate web and mobile deployments, and more.

I improved the performance and scalability of our CI/CD tooling, reducing engineering time between writing and releasing code.

• On the software side, I implemented async parallelization, request batching, and Redis caching to optimize the "code release sign-off" service logic, reducing endpoint response time by 60x.

• On the DevOps side, I split back-end services into specialized AWS EC2 instances (Puppet, Factor, internal AMIs) based on org budget and machine resources. This resolved resource limitations and allowed spinning up new servers with load balancing to handle traffic spikes (BIG-IP, NGINX).

I managed our internal Postgres database for storing build, test, and deployment data.

• Implemented a schema migration process (Flyway, Python scripts) coupled with code deploys to keep developer environments synchronized.

• Automated the data migration process for production and staging environments using Jenkins, Jailer, and Fabric/shell scripts.

• Routinely audited the database schema for performance gains. For example, I refactored the way we stored test timing data, eliminating over 100M rows and several complex SQL joins.

I addressed developer pain points by improving infrastructure reliability and making our tools easier to use.

• Collaborated with PMs/designers to conduct research sessions and build intuitive dev tools.

• Tracked test, bug, and environment health metrics (StatsD, Grafana) to exceed 99% uptime.

• Wrote and maintained extensive documentation and training labs in Confluence to quickly ramp up developers.

• Spearheaded development of a test reporting infrastructure tool to streamline web/mobile testing, report product health, and push Redfin towards continuous deployments. Built into Jenkins using Java and Bootstrap.js.

• Created Selenium tests to increase multi-browser coverage of home touring features. We improved pass rates by over 50% and replaced manual regression testing companywide.

As a part of the Science Data Management Systems group, my responsibilities involved analyzing, validating, transforming, and managing Earth and planetary science data.

For example:

• Designed and implemented a "Product Type Management Tool" web application to organize earth science Product Types and their component domains.

• For the front-end, built a Product Type directory UI and a form wizard with dynamic modal subforms for component domains. Built using JavaScript.

• For the back-end, implemented PHP authentication, JSON handlers, and Grails controller-service Groovy classes to create and modify Product Types via endpoints.

• Contributed code workaround to open-source Alpaca.js for instant form wizard tab validation.

As an intern in the Earth Science division, I had the privilege of:

• Rebuilding JPL’s Semantic Web for Earth and Environmental Terminologies (SWEET) website at 200k hits/month, using Drupal to achieve a responsive layout.

• Writing Python scripts (with ElementTree XML API) to parse and convert ontological OWL data into triple-formatted XML. We then fed the data into Apache Solr for indexing and built PHP endpoints to serve the data as JSON.

• Implementing an interactive force-directed graph (using D3.js) for visualizing 6000+ Earth science concepts in 200 ontologies. We built a screenshot feature (using SVG-Canvas conversion) as well as dynamic querying with breadcrumbs, faceted navigation, and data search with autocompletion.