Senior DataOps Engineer: Remote Data Ingestion & Cloud

Jpmorganchase; Municipio de Rincón de los Sauces; A distancia; ARS 137.157.000 - 228.596.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Contractor in USD

100% remote

Argentina holidays

English classes

Referral program

Learning platforms

Descripción de la vacante

Coderio is hiring a Senior Data Engineer focused on Data Ingestion and Integrations. You will design and implement scalable data collectors, connectors, and ingestion services, working directly with enterprise customers to understand environments, data sources, and security requirements.

You'll build reliable ingestion architectures using Python, Go, and modern tooling on AWS/Azure/GCP, Docker, and Kubernetes, contributing to DataOps best practices while enabling fast time-to-production in a

Formación

• Proficient in Python and Bash with strong SQL skills.
• Experience building data ingestion pipelines and data stores.
• Hands-on experience with AWS services and Terraform.
• Familiar with container-based deployments (Docker, Kubernetes).

Responsabilidades

• Design, develop, and maintain production-grade data collectors and ingestion services.
• Integrate enterprise data sources from IdPs, cloud, network, and security systems.
• Work with customers to translate environments and data flows into scalable solutions.
• Build connectors and ingestion pipelines for reliable production use.
• Collaborate across teams to improve time-to-value and operational efficiency.

Conocimientos

Python

Bash

SQL

Data pipelines

AWS

Terraform

GitHub

Docker

dbt

REST APIs

CI/CD

Herramientas

Docker

Kubernetes

REST APIs

Descripción del empleo

Coderio is hiring a Senior Data Engineer focused on Data Ingestion and Integrations. You will design and implement scalable data collectors, connectors, and ingestion services, working directly with enterprise customers to understand environments, data sources, and security requirements.

You'll build reliable ingestion architectures using Python, Go, and modern tooling on AWS/Azure/GCP, Docker, and Kubernetes, contributing to DataOps best practices while enabling fast time-to-production in a