
Developed the foundational Winery domain layer and REST API for the miw-upm/apaw-practice repository, enabling end-to-end winery operations and robust QA environments. Designed and implemented core data models for Evaluation, Reservation, TastingSession, and Wine, integrating MongoDB with UUID refactoring and seed data strategies. Leveraged Java and Spring Boot to deliver comprehensive API endpoints for managing tasting sessions, reservations, wines, pricing, and search functionality, all supported by automated unit and integration tests. Enhanced test reliability and data consistency, facilitating repeatable test environments and stable feature delivery. Applied domain-driven design, repository pattern, and test-driven development throughout the project lifecycle.
October 2025: Delivered foundational Winery domain layer and API, enabling end-to-end winery operations and reliable QA environments. Key contributions include establishing core data models (Evaluation, Reservation, TastingSession, Wine) with MongoDB mappings, UUID refactor, DAOs/Repositories, and seed data; implementing a comprehensive Winery REST API (endpoints for tasting sessions, reservations, wines, pricing, plus search) with robust tests; and QA improvements to stabilize tests and ensure consistent data setup. Business value: a scalable data foundation and API surface enabling faster feature delivery, reliable pricing updates, and repeatable test environments. Technical achievements: data modeling, repository pattern, seed strategy, REST API design, test automation, and search capabilities.
October 2025: Delivered foundational Winery domain layer and API, enabling end-to-end winery operations and reliable QA environments. Key contributions include establishing core data models (Evaluation, Reservation, TastingSession, Wine) with MongoDB mappings, UUID refactor, DAOs/Repositories, and seed data; implementing a comprehensive Winery REST API (endpoints for tasting sessions, reservations, wines, pricing, plus search) with robust tests; and QA improvements to stabilize tests and ensure consistent data setup. Business value: a scalable data foundation and API surface enabling faster feature delivery, reliable pricing updates, and repeatable test environments. Technical achievements: data modeling, repository pattern, seed strategy, REST API design, test automation, and search capabilities.

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