Acompañamos a nuestros clientes en su proceso de transformación digital a través de soluciones ágiles y de valor.
Ingeniero de Datos – Backend
Location
Colombia
Posted
3 days ago
Salary
0
Seniority
Senior
Job Description
Ingeniero de Datos – Backend
XpertGroup
• 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
Job Requirements
- Experiencia de 3-4 años
- Conocimientos en desarrollo de aplicaciones y plataformas orientadas a datos sobre AWS
- Conocimientos en diseño y consumo de soluciones analíticas utilizando Amazon Redshift, Athena, S3, Glue Data Catalog y servicios de integración de datos
- Desarrollo de APIs y microservicios con Node.js, TypeScript y Fastify
- Experiencia en procesamiento y análisis de datos, construcción de consultas SQL, integración con data lakes y data warehouse
- Conocimiento en calidad de datos, limpieza de datos, transformación de datos
- Conocimiento en Data Clean Rooms
- Estudios Universitarios / Carrera Profesional
Benefits
- Teletrabajo
- Oportunidades de desarrollo profesional
Related Guides
Related Job Pages
More Backend Engineer Jobs
• 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
• Build and evolve multi-gateway payment integrations: Design, implement, and maintain integrations with multiple payment gateway providers — including Stripe, PayPal, and others • Deliver full-stack payment experiences: Develop backend payment services and APIs in C#/.NET while building intuitive customer-facing experiences in React, Svelte, and TypeScript • Champion security, compliance, and resilience: Apply PCI-DSS best practices and resilient design patterns • Take an AI-first approach to building: Leverage AI-assisted development tools throughout the software lifecycle • Architect for scale and observability: Design and operate distributed, event-driven services on AWS and Kubernetes • Drive cross-functional execution: Translate business requirements into technical solutions



