Senior Staff Engineer (Data Infrastructure)

Join our team as a Senior Staff Engineer (Data Infrastructure) and take on the challenge of building the "Data Backbone" of our company. You will be responsible for the architecture, scaling, and reliability of the infrastructure that powers our Data Engineering and ML teams. Your goal is to provide a seamless, self-service environment for data scientists. You will manage high-throughput data tools, drive automation, build monitoring systems, support the ML lifecycle, and ensure reliability. You should have deep experience with Kubernetes, Trino, Ray, and other relevant tools.

• Architect and manage the lifecycle of high-throughput data tools including Trino, Ray, and JupyterHub on Kubernetes.
• Drive a "zero-manual-touch" philosophy using ArgoCD and Terraform to manage complex, stateful data environments.
• Build high-cardinality monitoring systems using VictoriaMetrics and Vector to track pipeline health, data ingestion rates, and system performance.
• Senior Leadership: You’ve spent time in the trenches. You’ve been on-call for 2:00 AM outages and have built the automation to ensure those outages never happen twice
• Self-Directed: You thrive in ambiguity. You can take a high-level requirement ("Make Trino faster") and turn it into a multi-week infrastructure roadmap
• Tooling Polyglot: You don't just use tools; you contribute to them. You are comfortable writing Go or Python to extend Kubernetes Operators or automate data workflows
• The "Data-Aware" Engineer: You understand that scaling a database or a Ray cluster is different from scaling a stateless API. You know how to handle persistent volumes and data gravity
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience