Problem

Users could access valuable data only through pre-built charts, limiting exploration, context, and discoverability. The existing interface made it difficult to understand relationships between creators, songs, and performance metrics.

Solution

I designed and implemented a Discovery section that exposed existing data in a navigable, contextualized format. The goal was to move from static visualization toward exploratory interaction, enabling users to drill into individual creators and songs.

Implementation

Using TypeScript and Next.js, I built reusable components and implemented dynamic routing so each creator and song had its own dedicated page. I experimented with server-side rendering and selectively shifted components to client-side rendering to improve initial load performance.

During development, inconsistencies in backend data surfaced, and I worked closely with backend and data engineers to clarify data contracts and determine what could be reliably displayed. I also implemented delayed loading and re-checking for slow assets (such as images), allowing content to appear as soon as it became available rather than blocking page load.

Problem

The platform needed a reliable way to ingest large volumes of crawled data, normalize it, and prepare it for downstream use—while handling delays, retries, and partial failures without corrupting stored data.

Solution

I designed and built an ingest server responsible for scheduling requests, receiving crawled data, extracting relevant fields, and transforming that data into predefined, queryable structures.

Implementation

Built with Python, Pydantic, and MongoDB, the server used asynchronous operations to manage multiple ingestion flows concurrently. I implemented retry logic with capped attempts to prevent runaway re-requests and ensured idempotent handling of partial data.

A significant focus was data integrity: filtering irrelevant fields, enforcing schemas with Pydantic, and ordering records for time-series use. I collaborated closely with the crawler operator to align request expectations and validate end-to-end behavior before releases.

Problem

New and existing franchise locations relied on developers to update basic public-facing information such as hours, address, and phone number. This created unnecessary engineering overhead and delayed updates to customer-visible content.

Solution

I designed and built a self-service location management interface that allowed authorized franchise owners to manage their own location data safely and independently. The interface replaced an earlier CRUD-style admin page with a task-based flow focused on common user goals, such as updating operating hours or publishing a new address.

Implementation

Built with Vue and TypeScript, the system required careful state management to ensure form data, validation, and save states remained consistent across tasks. I implemented role-based authorization so only permitted users could read or modify location data. The UI emphasized clarity and intent over raw data exposure.