Senior Data Ingestion & Cloud Integrations Engineer Remote

MercadoLibre, Inc.; Municipio de Rincón de los Sauces; Remote; ARS 185,966,000 - 278,949,000; Full time

Benefits offered by this job

USD payment

100% remote

Public holidays (Argentina)

English classes

Referral program

Learning platforms

Job summary

Darwoft is seeking a Senior Data Engineer focused on data ingestion, integrations, and collectors to bridge enterprise customers and engineering. This role goes beyond traditional backend work, blending data and software engineering, solution architecture, cloud infrastructure, and technical consulting.

You will design scalable ingestion architectures, build connectors, work with Python and/or Go, containers (Docker/Kubernetes), and deploy across AWS, Azure, and GCP.

Qualifications

• 10+ years of professional software/data engineering or related experience.
• Strong Python/Go coding and cloud deployment experience.
• Experience building data ingestion pipelines and integration platforms with enterprise data.

Responsibilities

• Design, develop, and maintain production-grade data collectors and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, network infrastructure, and SIEM systems.
• Work directly with customers to understand environments and data flows.
• Build scalable ingestion architectures for processing security events, logs, and identity activity.

Skills

Python

Go

REST APIs

Data ingestion

CI/CD

Distributed systems

Cloud platforms

Tools

Docker

Kubernetes

AWS

Azure

GCP

SQL

NoSQL

Job description

Darwoft is seeking a Senior Data Engineer focused on data ingestion, integrations, and collectors to bridge enterprise customers and engineering. This role goes beyond traditional backend work, blending data and software engineering, solution architecture, cloud infrastructure, and technical consulting.

You will design scalable ingestion architectures, build connectors, work with Python and/or Go, containers (Docker/Kubernetes), and deploy across AWS, Azure, and GCP.