Senior Data Engineer: Remote Ingestion & Integrations

Agileengine; Tandil; A distancia; ARS 136.863.000 - 197.692.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Contractor agreement with payment in $

100% remote work

Argentina's public holidays

English classes

Referral program

Access to learning platforms

Descripción de la vacante

Darwoft in LATAM is seeking a Senior Data Engineer focused on Data Ingestion, Integrations, and Collectors to bridge enterprise customers and engineering. This is a remote role with strong emphasis on scalable ingestion and security-conscious design.

You will work directly with customers to understand data sources, workflows, and APIs, then build reliable connectors, optimize performance, and drive time-to-value in large cloud-based environments.

Formación

• 10+ years in Software/Data/Platform engineering.
• Proficiency in Python and Go.
• Experience with data ingestion pipelines.
• Experience with cloud platforms (AWS/Azure/GCP).
• Customer-facing and solutions-focused.

Responsabilidades

• Design and maintain data collectors and ingestion services.
• Integrate enterprise data sources and APIs.
• Collaborate with customers to understand environments.
• Build scalable ingestion architectures for high-volume data.
• Deploy using REST, cloud services, and event-driven patterns.
• Work with Docker and Kubernetes in production.
• Troubleshoot deployments across app, infra, network, data.
• Contribute to product roadmap with integration insights.

Conocimientos

Python

Go

REST APIs

Data ingestion

Docker

Kubernetes

SQL & NoSQL

Cloud: AWS

Azure

GCP

CI/CD

Customer-facing

Autonomy

Herramientas

Git

CI/CD pipelines

Descripción del empleo

Darwoft in LATAM is seeking a Senior Data Engineer focused on Data Ingestion, Integrations, and Collectors to bridge enterprise customers and engineering. This is a remote role with strong emphasis on scalable ingestion and security-conscious design.

You will work directly with customers to understand data sources, workflows, and APIs, then build reliable connectors, optimize performance, and drive time-to-value in large cloud-based environments.