• Desarrollar aplicaciones y plataformas orientadas a datos sobre AWS • Diseñar y consumir soluciones analíticas utilizando Amazon Redshift, Athena, S3, Glue Data Catalog y servicios de integración de datos • Desarrollar APIs y microservicios con Node.js, TypeScript y Fastify • Procesar y analizar datos, construir consultas SQL, integrar con data lakes y data warehouse • Asegurar la calidad, limpieza y transformación de datos • Implementar Data Clean Rooms

• Design, develop, enhance, and maintain backend web applications using C#, .NET, and related technologies. • Build and support RESTful APIs, business services, and system integrations. • Write clean, scalable, maintainable code following software engineering best practices. • Collaborate with frontend developers to support React-based user experiences. • Troubleshoot, debug, and resolve application issues across development, testing, and production environments. • Participate in code reviews and contribute to development standards and technical quality. • Develop and execute unit, integration, and regression testing strategies. • Identify, diagnose, and resolve software defects and performance issues. • Ensure applications meet security, reliability, and scalability requirements. • Support deployment validation and production monitoring activities. • Participate in system design and software architecture discussions. • Recommend technical solutions that improve application performance, maintainability, and scalability.

• Participate in the development and maintenance of an innovative application. • Analyze requirements (in collaboration with the client) and contribute to solution design. • Develop test cases. • Deploy applications to production environments. • Diagnose and troubleshoot incidents. • Use repositories and software development tools. • Design and develop new application modules. • Apply AI-driven approaches for: Code generation and refactoring, Automated documentation, Test generation and validation, Debugging and root-cause analysis, Code reviews and quality improvements, SDLC automation and developer productivity optimization. • Understand the capabilities, limitations, and appropriate usage of Large Language Models (LLMs) in software engineering workflows. • Collaborate in the adoption of AI engineering best practices, governance, and secure usage of AI tools in enterprise environments. • Stay up to date with emerging AI engineering trends, frameworks, and development accelerators.

• Participate in the development and maintenance of an innovative application • Analyze requirements (in collaboration with the client) and contribute to solution design • Develop test cases • Deploy applications to production environments • Diagnose and troubleshoot incidents • Use repositories and software development tools • Design and develop new application modules • Apply AI‑driven approaches for: Code generation and refactoring, Automated documentation, Test generation and validation, Debugging and root‑cause analysis, Code reviews and quality improvements, SDLC automation and developer productivity optimization • Understand the capabilities, limitations, and appropriate usage of Large Language Models (LLMs) in software engineering workflows • Collaborate in the adoption of AI engineering best practices, governance, and secure usage of AI tools in enterprise environments • Stay up to date with emerging AI engineering trends, frameworks, and development accelerators