Senior Data Engineer – Ingest & Integrations (Remote Latam)

Unavailable; La Pampa; Teletrabalho; ARS 181 747 000 - 272 620 000; Tempo integral

Resumo da oferta

Darwoft is seeking a Senior Data Engineer (Python/Go) focused on data ingestion, integrations, and collectors, bridging enterprise customers and engineering. You’ll design scalable ingestion pipelines, connectors, and integration services across cloud environments and security platforms.

The role requires extensive experience with Python/Go, REST APIs, and distributed systems. You’ll collaborate with customers, architects, and product teams to ensure reliable, scalable data flows and timely

Qualificações

• 10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.
• Strong software development experience with Python and Go.
• Strong experience designing and consuming REST APIs.
• Hands-on experience building data ingestion pipelines, connector frameworks, integration platforms, or similar systems.
• Experience integrating complex enterprise systems and third-party platforms.
• Solid understanding of both SQL and NoSQL databases.
• Production experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience working with Docker and Kubernetes.
• Strong understanding of Git-based development workflows and CI/CD practices.
• Experience designing reliable, scalable, and production-ready distributed systems.
• Strong debugging skills across APIs, infrastructure, networking, application services, and data pipelines.
• Experience working directly with customers, stakeholders, or technical partners.
• Ability to translate complex customer requirements into pragmatic technical solutions.
• Strong communication skills and the ability to operate effectively in customer-facing technical conversations.
• High degree of autonomy and ownership when solving ambiguous technical problems.

Responsabilidades

• Design, develop, and maintain production-grade data collectors, connectors, and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, SASE solutions, network infrastructure, endpoints, applications, security platforms, and SIEM systems.
• Work directly with enterprise customers to understand environments, data flows, APIs, security requirements, and integration constraints.
• Participate in technical onboarding processes, from discovery and architecture design to deployment.
• Design scalable ingestion architectures for processing security events, logs, identity activity, network telemetry, and other high-volume data sources.
• Build integrations using REST APIs, cloud-native services, event-driven architectures, and modern software engineering practices.
• Develop backend services primarily using Python and/or Go.
• Work with SQL and NoSQL databases to store, transform, query, and analyze high-volume data.
• Build and operate containerized services using Docker and Kubernetes.
• Deploy and integrate solutions across AWS, Azure, and GCP environments.
• Troubleshoot complex customer deployment and integration issues across application, infrastructure, networking, API, and data layers.
• Optimize ingestion performance, reliability, scalability, and operational efficiency.
• Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering teams.
• Act as a trusted technical advisor around customer data architecture, collection strategies, security integrations, and implementation best practices.
• Identify recurring customer requirements and transform them into reusable connectors, platform capabilities, or improvements to the core product.
• Contribute technical insights from real-world implementations to the product roadmap.
• Support production adoption and continuously improve time-to-value for enterprise customers.
• Participate in occasional customer-facing technical sessions and, when necessary, onsite engagements.

Conhecimentos

Python

Go

REST APIs

Data ingestion

Cloud platforms

Docker

Kubernetes

Ferramentas

Docker

Kubernetes

Descrição da oferta de emprego

• Location: LATAM
• Work Model: 100% Remote
• Project: Identity Security / Cybersecurity Platform
• Seniority: Senior
• Engagement: Full-time

143L - Senior Data Engineer (Python/Go/Data Ingestion/Cloud) · Remote · LATAM

• Location: LATAM
• Work Model: 100% Remote
• Project: Identity Security / Cybersecurity Platform
• Seniority: Senior
• English Level: B2 / C1
• Engagement: Full-time

Get to Know Darwoft

At Darwoft, we build custom software solutions and partner with international companies to create high-impact digital products.

We are a Latin American technology company with a people-first culture, strong professional standards, and a long-term partnership mindset. We work with distributed teams, complex technical challenges, and clients whose technology has a direct impact on their businesses and users.

About the Project

We are partnering with an innovative cybersecurity company building a next-generation Identity Security and Identity Observability platform .

The product helps enterprise security teams understand how human users, service accounts, workloads, applications, and AI-driven identities access systems across cloud, SaaS, network, endpoint, and on-premise environments .

At the core of the platform is a highly data-intensive architecture that collects and analyzes large volumes of events, logs, network telemetry, identity activity, and security signals . This information is processed to identify unusual access patterns, security risks, identity blind spots, infrastructure misconfigurations, and potential threats.

The platform integrates with complex enterprise ecosystems including identity providers, cloud platforms, SASE solutions, SIEMs, endpoint security tools, network infrastructure, and security services.

About the Role

We're looking for a Senior Data Engineer focused on Data Ingestion, Integrations, and Collectors to become a key technical bridge between enterprise customers and the engineering organization.

This is not a traditional backend or internal data engineering position.

You'll work directly with customers to understand their infrastructure, data sources, security architecture, network topology, APIs, and workflows, then design and implement scalable mechanisms to ingest that information into the platform.

You'll combine data engineering, software engineering, solution architecture, cloud infrastructure, and technical consulting .

A major part of your mission will be building and evolving connectors and ingestion pipelines capable of integrating data from complex enterprise environments while maintaining reliability, scalability, security, and fast time-to-production.

What You'll Be Doing

• Design, develop, and maintain production-grade data collectors, connectors, and ingestion services .
• Integrate enterprise data sources including identity providers, cloud platforms, SASE solutions, network infrastructure, endpoints, applications, security platforms, and SIEM systems .
• Work directly with enterprise customers to understand their environments, data flows, APIs, security requirements, and integration constraints.
• Participate in technical onboarding processes, from initial discovery and architecture design through production deployment.
• Design scalable ingestion architectures for processing security events, logs, identity activity, network telemetry, and other high-volume data sources .
• Build integrations using REST APIs, cloud-native services, event-driven architectures, and modern software engineering practices .
• Develop backend services primarily using Python and/or Go .
• Work with SQL and NoSQL databases to store, transform, query, and analyze high-volume data.
• Build and operate containerized services using Docker and Kubernetes .
• Deploy and integrate solutions across AWS, Azure, and GCP environments .
• Troubleshoot complex customer deployment and integration issues across application, infrastructure, networking, API, and data layers.
• Optimize ingestion performance, reliability, scalability, and operational efficiency.
• Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering teams.
• Act as a trusted technical advisor around customer data architecture, collection strategies, security integrations, and implementation best practices.
• Identify recurring customer requirements and transform them into reusable connectors, platform capabilities, or improvements to the core product.
• Contribute technical insights from real-world implementations to the product roadmap.
• Support production adoption and continuously improve time-to-value for enterprise customers.
• Participate in occasional customer-facing technical sessions and, when necessary, onsite engagements.

What You Bring

• 10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.
• Strong software development experience with:
  • Python
  • Go
• Strong experience designing and consuming REST APIs .
• Hands‑on experience building data ingestion pipelines, connector frameworks, integration platforms, or similar systems .
• Experience integrating complex enterprise systems and third‑party platforms.
• Solid understanding of both SQL and NoSQL databases .
• Production experience with at least one major cloud platform:
  • AWS
  • Azure
  • GCP
• Experience working with Docker and Kubernetes .
• Strong understanding of Git-based development workflows and CI/CD practices .
• Experience designing reliable, scalable, and production-ready distributed systems.
• Strong debugging skills across APIs, infrastructure, networking, application services, and data pipelines.
• Experience working directly with customers, stakeholders, or technical partners.
• Ability to translate complex customer requirements into pragmatic technical solutions.
• Strong communication skills and the ability to operate effectively in customer‑facing technical conversations.
• High degree of autonomy and ownership when solving ambiguous technical problems.

Highly Relevant Experience

Experience with any of the following will be especially valuable:

• Identity and Access Management (IAM )
• Identity Providers (IdPs)
• Identity Security
• Cybersecurity platforms
• SIEM systems
• Security telemetry
• Network security
• Endpoint security
• SASE / Zero Trust environments
• Cloud security
• Large-scale event processing
• Streaming architectures