UJET
Embedded Analytics Engineer
September 2024 - Present • San Francisco Bay Area, United States - Remote
- Operated and enhanced a multitenant embedded analytics platform using Looker, LookML, MySQL, and GitHub CI, serving 52 customers and 300+ hourly users with 50+ dashboards and real-time data refreshing every 20 seconds, processing 200k+ queries per hour for a B2B SaaS CCaaS company.
- Optimized query performance and reduced infrastructure costs by implementing LookML best practices, refactoring legacy code for performance improvements, and building monitoring and alerting systems—reducing average query runtimes by 55% and database query volume by 75% to improve user experience across the platform.
- Increased metrics reliability by developing a full unit test suite for LookML transformations and implementing CI validation for dashboard rendering. Established semantic standards and LLM-based documentation to enable end users to quickly understand data models within the self-service BI platform.
- Leading migration of 100+ LookML views to dbt models and transitioning from MySQL to BigQuery to enhance product capabilities and query performance.
Tech Stack: Looker, BigQuery, MySQL, dbt, GitHub CI, LookML
Cloud-native CCaaS platform powered by AI, unifying omnichannel support with automation and intelligence.