Senior Data Ingestion Engineer (Remote LATAM)

Applaudo; Municipio de Rincón de los Sauces; Remote; ARS 184,482,000 - 276,723,000; Full time

Benefits offered by this job

Contractor/pay USD

100% remote work

Argentina holidays

English classes

Referral program

Learning platforms

Job summary

Darwoft is seeking a Senior Data Engineer to drive data ingestion and integrations for an Identity Security platform. You will work closely with customers to design scalable collectors, connectors, and ingestion pipelines across cloud and on-prem environments.

You will apply Python/Go expertise, build robust data workflows, and collaborate with cross-functional teams to ensure secure and reliable data processing at scale.

Qualifications

• ,10+ years of professional software/data/platform engineering experience.
• Strong experience building data ingestion pipelines and integration platforms.
• Proficient with Python and Go codebases; comfortable with cloud services.

Responsibilities

• Design, develop, and maintain production-grade data collectors, connectors, and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, SASE solutions, and SIEM systems.
• Collaborate with customers to understand environments, data flows, APIs, and integration constraints.
• Build scalable ingestion architectures for processing security events, logs, and network telemetry.
• Develop backend services using Python and/or Go and work with SQL/NoSQL databases.
• Containerize services with Docker and deploy on Kubernetes clusters.

Skills

Python

Go

REST APIs

Data ingestion

SQL

NoSQL

Distributed systems

CI/CD

Cloud platforms

Tools

Docker

Kubernetes

Job description

Darwoft is seeking a Senior Data Engineer to drive data ingestion and integrations for an Identity Security platform. You will work closely with customers to design scalable collectors, connectors, and ingestion pipelines across cloud and on-prem environments.

You will apply Python/Go expertise, build robust data workflows, and collaborate with cross-functional teams to ensure secure and reliable data processing at scale.