About the Job
As a Data Platform Engineer, Infrastructure, you will build and operate the cloud foundation the entire data platform runs on — the systems every robot log, dashboard, and model-training run depends on. You will collaborate with pipeline and analytics engineers, as well as edge and robotics teams, to keep the platform reliable, secure, and cost-efficient as our fleet grows.
About the Data Platform Team
What You'll Get To Do
- Design, build, and operate the cloud infrastructure for the data platform: compute (Kubernetes, serverless, batch clusters), storage (object stores, warehouse/lakehouse), and networking.
- Manage everything as code: Terraform/IaC, GitOps workflows, and CI/CD for infrastructure and data services.
- Provision and tune infrastructure for heavy workloads: large-scale sensor data processing, distributed pipeline execution, and ML training and evaluation jobs.
- Own platform reliability: SLAs/SLOs, on-call practices, incident response, and capacity planning as fleet data volume grows.
- Implement security and governance: IAM and access controls, secrets management, encryption, audit logging, and environment isolation.
- Own cloud cost management: monitoring, budgeting, and optimization across storage and compute.
- Build the observability stack (metrics, logging, tracing) for all data platform services.
- Build internal tooling and paved paths so pipeline and analytics engineers can ship without becoming infrastructure experts.
What You Have
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- 3–5+ years of experience in infrastructure, platform, DevOps, or SRE roles, ideally supporting data-intensive systems.
- Strong experience with a major cloud (AWS or GCP), Kubernetes, and infrastructure-as-code (Terraform or similar).
- Strong programming skills in Python, Go, or similar for automation and internal tooling.
- Experience operating production systems: monitoring, alerting, incident response, and capacity planning.
- Working knowledge of data infrastructure components (warehouses, object storage, streaming systems, orchestrators) and what they demand from underlying infrastructure.
- Experience with security fundamentals: IAM, network security, secrets management.
- Strong problem-solving skills and ability to work in interdisciplinary teams.
The Extras That Set You Apart
- Experience supporting data or ML platforms specifically (Spark/Databricks clusters, GPU scheduling, feature stores).
- Experience with high-volume telemetry or IoT/edge fleets.
- Track record of significant cloud cost optimization.
- Prior experience as an early platform/infrastructure hire, building from zero.