Senior Platform Software Engineer, Transport

dbt Labs dbt Labs · Data AI · United States · Remote · Engineering

dbt Labs is seeking a Senior Platform Software Engineer to join their Transport team, focusing on building and operating foundational platform infrastructure for their cloud services. This role involves architecting and developing components for service routing, cloud networking, and customer migration tooling within a multi-cell architecture. The engineer will write backend services in Go and Python, automate infrastructure using tools like Kubernetes and Terraform, and collaborate with various teams. The role emphasizes ownership, troubleshooting complex distributed systems, and contributing to a scalable, reliable platform that supports AI use cases.

What you'd actually do

  1. Architect and build platform infrastructure: Design, build, and operate foundational components of our multi-cell platform, including service routing, cloud networking, and the control plane for managing account lifecycles.
  2. Drive seamless migrations: Develop and automate the tooling to migrate customer accounts from legacy environments to the new multi-cell architecture at scale.
  3. Develop scalable backend services: Write robust, high-quality backend services and infrastructure code, primarily in Go and Python, with opportunities to work with Rust.
  4. Tackle cloud networking challenges: Collaborate on network architecture design, including VPC management, load balancing, DNS, PrivateLink, and service mesh configurations to support single-tenant and multi-tenant deployments.
  5. Automate for scale: Design and implement automation using tools like Argo Workflows, Kubernetes, and Terraform to enhance the reliability, efficiency, and scalability of our platform.

Skills

Required

  • backend or platform engineering
  • Go or Python
  • large-scale distributed systems
  • modern cloud infrastructure
  • AWS, GCP, or Azure
  • Docker
  • Kubernetes
  • Terraform
  • internal platforms and automation
  • cloud networking concepts
  • load balancing
  • DNS
  • VPCs
  • proxies
  • service mesh technologies
  • end-to-end ownership
  • systematic, customer-focused approach
  • proactive and collaborative communication

Nice to have

  • cell-based or multi-tenant architectures
  • tooling for large-scale account migrations
  • internal developer platforms
  • self-service infrastructure
  • nginx
  • Istio
  • Envoy
  • AWS Transit Gateway
  • PrivateLink
  • Kubernetes CNI/service mesh implementations
  • multi-cloud strategies
  • Rust
  • AWS Certified Solutions Architect – Professional
  • AWS Advanced Networking Specialty
  • Certified Kubernetes Administrator
  • contributions to open-source cloud-native projects

What the JD emphasized

  • building large-scale distributed systems
  • extensive hands-on experience with a major cloud provider (AWS, GCP, or Azure)
  • extensive hands-on experience with both Go and Python