Senior Data Platform Engineer – Scalable Distributed Systems

Coreweave; Oregon; Híbrido; USD 215.000 - 254.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical insurance

Dental insurance

Vision insurance

Life Insurance

ESPP

401(k) plan

Paid parental leave

Flexible PTO

Descripción de la vacante

CoreWeave, Inc. is seeking a Senior Engineer I to design and build large-scale data ingestion, storage, and analytics systems. You will architect distributed services, implement APIs in Go, Python, and TypeScript, and operate on Kubernetes-based infrastructure across GCP/AWS/Azure.

You will mentor junior engineers, collaborate with product and revenue teams, and focus on secure, scalable, and cost-efficient data platforms applicable to petabyte-scale datasets.

Formación

• Bachelor's degree in Computer Science or related STEM field with 5 years of experience
• Proficient in Go and Python for live systems
• Experience deploying with Kubernetes and Docker
• Experience on cloud platforms (GCP/AWS/Azure) with distributed systems
• Experience with MySQL or PostgreSQL and Kafka/PubSub

Responsabilidades

• Design, develop, and maintain large-scale ingestion, storage, and querying systems
• Architect distributed backend services for performance and cost-efficiency
• Build and operate APIs using Go, Python, TypeScript
• Mentor junior engineers and review code
• Collaborate with product, revenue, and engineering to define requirements

Conocimientos

Go

Python

TypeScript

API design

Distributed systems

Educación

Bachelor's degree in Computer Science or related STEM

Herramientas

Kubernetes

Docker

MySQL

PostgreSQL

Kafka/PubSub

Terraform

GCP

AWS

Azure

Descripción del empleo

CoreWeave, Inc. is seeking a Senior Engineer I to design and build large-scale data ingestion, storage, and analytics systems. You will architect distributed services, implement APIs in Go, Python, and TypeScript, and operate on Kubernetes-based infrastructure across GCP/AWS/Azure.

You will mentor junior engineers, collaborate with product and revenue teams, and focus on secure, scalable, and cost-efficient data platforms applicable to petabyte-scale datasets.