Cloud Engineer (DevOps)

Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.

With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.

We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.

We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.

🚀 We build and scale our own brands.

🦾 We invest in AI and automation like few others in eCom.

📈 We test fast, grow fast, and help you do the same.

🤝 Be part of a dynamic, diverse, and talented global team.

🌍 100% Remote, USD competitive salary, paid time off, and more.

We are seeking a Data Cloud Engineer (DevOps + DataOps) to design, build, and maintain our AWS-based cloud infrastructure and data pipelines. You’ll ensure scalability, security, and efficiency across mission-critical systems while driving automation and modern DevOps practices. This is a hands-on role with the opportunity to own infrastructure projects end-to-end, mentor peers, and introduce best practices that power data-driven decision-making at global scale.

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  Cloud Infrastructure (AWS): Design, deploy, and optimize AWS environments (S3, RDS, Redshift, DynamoDB, Glue, EMR, Lambda, ECS, etc.).

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  Data Pipelines: Build and manage robust ETL workflows and scalable data architectures.

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  Automation & DevOps: Implement Infrastructure as Code (Terraform/Terragrunt) and integrate CI/CD pipelines.

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  Containerization: Deploy applications with Docker and Kubernetes.

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  Security & Compliance: Apply cloud security best practices across all environments.

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  Collaboration: Partner with BI, data, and development teams for seamless deployments.

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  Troubleshooting: Diagnose and resolve cloud and data-related issues with agility.

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  Knowledge Sharing: Contribute to team learning and mentor junior engineers.