Daye Karibi-Whyte

Real-Time Data Analytics Pipeline

• Architected and deployed an end-to-end data pipeline using SQL and internal automation tools, reducing data latency from over 3 days to under 1 hour.
• Increased data granularity by 100x (from daily to 15-minute intervals), enabling fine-grained, real-time analysis for the first time on the team.
• Resolved critical data integrity bugs, including timestamp misalignments and duplication errors, to ensure high data accuracy and build stakeholder trust.
• Discovered and reported a critical bug in a legacy production database, improving data accuracy for multiple dependent teams across the organization.
• Built and launched two real-time analytics dashboards to visualize granular, container-level resource costs, enabling faster data-driven optimizations.

AI-Powered Anomaly Analysis Tool

• Took initiative to develop a proof-of-concept AI agent in Python to automate root cause analysis, reducing manual alert investigation from hours to minutes.
• Engineered the successful integration of a Large Language Model (LLM) API, an issue-tracking API, and a distributed database API.
• Authored a comprehensive design document and strategic roadmap for deploying the tool on the company's large-scale container orchestration platform.

2024

• Built AI tool for Flutter @ Google team to generate code from UI images.
• Enhanced prompt engineering for AI tool, improving code-to-UI accuracy.
• Automated image capture and comparison for AI-generated code (bash, Docker, Python).

2023

• Developed a full-stack communication feature for Google Workspace Enterprise to enable direct interaction between users and administrators.
• Implemented a backend RPC service to efficiently query and retrieve user data from Google Spanner, a globally distributed database.
• Integrated the backend data service with the frontend UI to create a seamless and responsive user experience.
• Translated a comprehensive technical design document into a fully functional and deployed product feature.