Senior Data & Full-Stack Engineer (Python/Django + AWS)

Pearson; Santa Fe (NM); Presencial; USD 80.000 - 90.000; Jornada completa

Descripción de la vacante

Pearson is seeking a Data Engineer / Full Stack Engineer in the United States, with strong Python-based backend and modern frontend experience. The role combines building scalable APIs, data pipelines, and serverless cloud services, using Django/DRF, Nuxt/Vue, and AWS

Ideal candidates will transform data, implement secure auth, and collaborate in an Agile distributed environment across backend, frontend, and data engineering teams.

Formación

• Experience building Python-based backends with Django/DRF.
• Strong frontend work with Nuxt 4 / Vue 3 / TypeScript.
• Familiarity with AWS services, serverless and infrastructure.
• Data pipelines, ETL/ELT, and data transformation experience.
• Ability to design scalable RESTful APIs and secure auth.

Responsabilidades

• Design, develop, and maintain scalable backend services in Python/Django.
• Build RESTful APIs with DRF/OpenAPI/Swagger documentation.
• Create data pipelines and ETL/ELT workflows using AWS Glue and Python tools.
• Develop frontend interfaces with Nuxt 4, Vue 3, and TypeScript.
• Implement secure authentication with django-rest-knox, OAuth and Azure AD.
• Manage cloud infra with AWS CDK (Python) and Terraform.
• Ensure quality with unit, integration, and load testing.

Conocimientos

Python

Django/DRF

Nuxt/Vue

AWS

REST APIs

CI/CD

Terraform

Docker

GitHub Actions

OpenAPI/Swagger

Herramientas

AWS CDK (Python)

Terraform

Docker

GitHub Actions

OpenAPI/Swagger

Descripción del empleo

Pearson is seeking a Data Engineer / Full Stack Engineer in the United States, with strong Python-based backend and modern frontend experience. The role combines building scalable APIs, data pipelines, and serverless cloud services, using Django/DRF, Nuxt/Vue, and AWS

Ideal candidates will transform data, implement secure auth, and collaborate in an Agile distributed environment across backend, frontend, and data engineering teams.