Memo Ramirez

• ›Built Airflow DAGs for live game data ingestion that compute per-quarter and full-game metrics consumed by the Analytics Team.
• ›Designed and shipped an extensible ingestion service that unifies player, league, and team data from disparate sources, abstracting away both source type (CSV, API, etc.) and entity type so new providers can be onboarded with minimal code.
• ›Implemented duplicate-detection auditing across overlapping data sources — including profile-image matching for hard-to-resolve player records and cosine-similarity techniques inspired by published player-ID matching research (e.g., American Soccer Analysis Glass Onion, Unravel Sports).
• ›Continuously refined ingestion quality, observability, and operational processes for the data platform.

Continuing as a consultant in the same capacity.

• ›Worked across the stack: shipped React features on the front end, updated/extended the company's Go-based API Gateway on the back end, and developed data pipelines for specific client projects.
• ›Built a daily Airflow data pipeline supporting a new business acquisition, ingesting external provider data for leads, client status, and staff tasks into the company's analytics stack.

• ›Owned work across the SDLC while mentoring software and data engineers.
• ›Drove deployment frequency from one large release every two months to small releases every week, averaging 2.52 deployments per sprint, by improving review and release processes.
• ›Established and built a GraphQL Federated API Gateway in Go, improving performance and data-exchange between front-end clients and backend services.
• ›Architected data pipeline, in Java, for ATS and HRIS data ingestion from several external ATS providers.

• ›Developed a micro-frontend architecture that improved application performance and simplified data exchange between front- and back-end services.
• ›Built a knowledge-center service in React + TypeScript backed by a headless CMS, streamlining content publishing and lifting user engagement.

• ›Delivered high-traffic web and mobile apps for McDonald's — including the brand's most successful digital promotion at the time — recognized by multiple third-party industry awards.
• ›Built a Node.js (NestJS) middleware service in TypeScript with RxJS for an internal client tool supporting national retail-promotion operations.
• ›Contributed to internal SaaS applications in Java (RxJava, Vert.x) and PHP (Laravel).

• ›Architected and built a proprietary data-analytics API using a microservice pattern in Java Spring Boot.
• ›Developed data pipelines in Java Spring and Python to ensure clients can bench-test advertising campaigns — recognized with a company-wide award.
• ›Developed web applications in Angular, React, and PHP (WordPress, Laravel).