Data Cloud Engineer (DataOps)

About Nimbus Data Systems Nimbus Data Systems 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. Why Nimbus Data Systems 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. Key Responsibilities The mission of the Data Cloud Engineer is to design, implement, and maintain scalable, secure, and cost-effective cloud infrastructure and data pipelines on AWS . This role combines DevOps and DataOps practices to ensure seamless infrastructure automation, data management, and deployment workflows. The engineer will collaborate cross-functionally with data, BI, and development teams to support critical business needs while proactively identifying improvements in automation, security, and cost efficiency. Design, deploy, and optimize AWS cloud infrastructure (S3, Redshift, Lambda, ECS) for scalability and performance. Build and maintain data architectures and ETL pipelines supporting BI and analytics. Implement Infrastructure as Code (Terraform, Terragrunt) and manage CI/CD pipelines for automation. Use Docker and Kubernetes to enable containerized, reliable deployments. Ensure cloud security, compliance, and cost efficiency across environments. Collaborate with engineering and data teams to resolve issues and enhance workflows. Document best practices and share expertise to strengthen the team’s capabilities. Requirements 3+ years of experience as a Cloud, DevOps, or Data Engineer. Deep expertise with AWS services (S3, Redshift, Glue, Lambda, EMR, ECS, RDS, DynamoDB). Strong background in data architecture, ETL design, and automation. Proficiency in Terraform/Terragrunt for IaC and CI/CD pipeline management. Knowledge of Docker, Kubernetes, and container orchestration. Understanding of cloud security frameworks and compliance standards. Solid scripting skills in Python or Bash. Strong communication, collaboration, and problem-solving skills. A mindset of ownership, curiosity, and continuous learning. Originally posted on Himalayas