Currently a tech lead for the Marketplace Data Observability team, which manages pipelines for processing high volumes of business-critical ads data and curating analytical interfaces.Technical domain includes* Distributed Systems* Batch/Stream Processing* Logging* Data Schematization, Modeling, Observability, & Warehousing* Job Orchestration Business domain includes* Ad Metrics* Ad Attribution* Advertiser Billing* Ad Delivery Monetization* Bot FilteringMentorship: I've guided many engineers (NA + EU) during their onboarding, projects (design/scoping/prioritization), and oncall shifts. Incident response: We're one of the most oncall-heavy teams at Yelp, and I've been responsible for accurately assessing the (financial) impact of many incidents, quickly resolving them, writing postmortems, making our systems more failure-resilient in response, and giving feedback to Yelp's infra/platform teams so that they can better support us.

Team: Ads BackendSimplified campaign management for advertisers with multiple budgets (i.e. regular + promotional), allowing bids to be set more efficiently:* Created a new MySQL table for representing ad campaign budget changes and a Cassandra table for representing an ad campaign's spend within a specific budget period* Created APIs for querying/updating the above tables (i.e. performing budget edits, getting spend info, etc)Languages: Python

Team: Ads BackendDeveloped a package for logging user interactions with Yelp ads (impressions and clicks) so that new ad products could be monetized quickly and safely:* Implemented schema validation for heavily nested revenue-critical logs, thereby reducing the risk of malformed data entering Yelp’s ads systems* Ran performance tests to ensure that the package had a tolerable impact on page load times* Rolled the package out to 100% of ad traffic and added SignalFx metrics reporting to make it easier to detect logging issues in the future* Used Spark to compare data produced by the package against data produced by the legacy systemLanguages: Python

Team: Game ServicesDeveloped an API for searching usernames and retrieving player info within popular games:* Implemented a new endpoint that allows you to retrieve information about a player by supplying either an exact or partial name* Utilized an Elasticsearch-backed service for the partial-matching aspect of this endpoint, and created an SQS workflow for indexing player data in Elasticsearch* Performed various performance tests using JMeter and optimized reads/writesMade performance improvements to a graph-based service that managed player relationships:* Modularized SQS consumers and redeployed them with separate autoscalingLanguages: Go, Java

Team: Video Player & DashboardMade several improvements to Vidyard's video player, focusing on user experience and metrics reporting:* Simplified code for video playback, reducing load times on desktop and mobile* Identified and fixed issues where video engagement data wasn't being properly reported during video playback* Refactored code that controlled the player's responsiveness under different screen resolutions, improving the user experience on mobile* Improved the player's accessibility, localization, and cross-device/browser compatibility* Redesigned existing player components and expanded customization optionsLanguages: JavaScript, CSS/HTML, and Ruby on Rails

Team: Subscriber Policy BrokerDesigned and developed the first REST API for the Subscriber Policy Broker and prepared its integration with Sandvine's new microservice architecture:* Implemented over 30 endpoints and various framework components. Wrote tests using JUnit.* Collaborated with other platform teams to standardize on service discovery, authentication, documentation, metric collection, and error handlingLanguages: Java