Senior Data Engineer - Remote Ingest & Integrations

Epam Systems Inc; Ciudad de Mendoza; Remote; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Contractor agreement with payment in $

100% remote work

Argentina's public holidays

English classes

Referral program

Access to learning platforms

Job summary

Darwoft is seeking a Senior Data Engineer focused on data ingestion, integrations, and connectors. You will partner with enterprise customers to design scalable ingestion pipelines, integrate diverse data sources, and build reliable, production-ready services.

You will work across cloud platforms (AWS, Azure, GCP), containerized environments (Docker/Kubernetes), and modern data tech stacks, while translating customer requirements into pragmatic solutions and driving time-to-value for deployments.

Qualifications

• 10+ years of professional software or data engineering experience.
• Strong experience with Python and Go.
• Experience designing and consuming REST APIs.
• Experience with cloud platforms (AWS, Azure, GCP).

Responsibilities

• Design, develop, and maintain data collectors, connectors, and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, SASE, SIEM.
• Work with customers to understand environments and data flows.
• Design scalable ingestion architectures for security events and logs.
• Build integrations using REST APIs, cloud-native services, event-driven patterns.
• Develop backend services in Python and/or Go.

Skills

Python

Go

REST APIs

Data ingestion

Cloud platforms

Docker & Kubernetes

SQL / NoSQL

Customer-facing

Communication

Distributed systems

CI/CD

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Darwoft is seeking a Senior Data Engineer focused on data ingestion, integrations, and connectors. You will partner with enterprise customers to design scalable ingestion pipelines, integrate diverse data sources, and build reliable, production-ready services.

You will work across cloud platforms (AWS, Azure, GCP), containerized environments (Docker/Kubernetes), and modern data tech stacks, while translating customer requirements into pragmatic solutions and driving time-to-value for deployments.