Design állás, munka

• Design and develop cloud-native data processing pipelines, microservices, and APIs using Java (17+) / Spring Boot.
• Integrate with enterprise data platforms via messaging frameworks such as RabbitMQ or Zeebe.
• Deploy, monitor, and operate applications in public cloud environments (Azure preferred).

• Performance Optimization – Important for large datasets, but not critical for small reports.
• Accessibility (a11y) – Recommended for enterprise or public-facing apps.
• Testing (Jest/Cypress) – Good for production reliability, but not mandatory for MVP.

• Triaging new requirements, assessing their impact, and providing estimates for modifying data models accordingly.
• You will also be responsible for developing and enhancing business physical data models to meet evolving needs while driving alignment as necessary.

Bridge Between Tech and Stakeholders: Act as intermediaries between engineering teams and stakeholders, ensuring clean, transformed datasets. Understand business requirements and translate them into technical specifications...

• ETL Pipeline Development: Develop, optimize, and maintain ETL pipelines to efficiently extract, transform, and load data from various sources, ensuring high data quality.
• Monitor and troubleshoot production data pipelines, ensuring their performance and reliability.

• Weboldalak, webes alkalmazások fejlesztése
• Internetes alkalmazások fejlesztése
• Belső használatú adminisztratív és BI rendszerek fejlesztése
• Együttműködés a backend fejlesztőkkel
• Fejlesztéshez kapcsolódó dokumentáció készítése, egyéb adminisztratív feladatok elvégzése
• Elvégzett fejlesztések tesztelése