Staff SDET: Data Connectors & High-Scale Ingestion

Veeam Software; San Jose (CA); On-site; USD 250,000 - 465,000; Full time

Benefits offered by this job

Unlimited PTO

Paid holidays

Health coverage

401(k) matching

Volunteer time

Job summary

Veeam Software in the United States is seeking a Staff Software Development Engineer in Test (SDET) specializing in Data Connectors and High-Scale Ingestion. You will design testing frameworks and benchmarking tools to validate multi-source data pipelines across AWS, Azure, and Kubernetes.

You will build automation suites for ingestion connectors (REST, gRPC, Kafka) and implement fault-injection with high-concurrency clusters.

Qualifications

• 8+ years of software testing/SDET experience in C++, Java, Go, or Python.
• Deep experience testing streaming architectures (Kafka, Event Hubs), queues, and API protocols (gRPC, WebSockets, REST).
• Hands-on proficiency with AWS, Azure, and Kubernetes and building distributed load-generation tools.

Responsibilities

• Design scalable performance, backpressure, and stress-testing harnesses for ingestion connectors (REST, gRPC, CDC, Kafka, RabbitMQ).
• Build automation suites across AWS and Azure to test real-world data flows under degraded networks and high concurrency.
• Implement automated fault-injection pipelines to guarantee zero-data-loss execution.
• Utilize Kubernetes to orchestrate transient, high-concurrency test clusters and mock endpoints at scale.

Skills

SDET experience

Streaming architectures

API protocols

Cloud platforms

Programming languages

Tools

AWS

Azure

Kubernetes

Locust

k6

Job description

Veeam Software in the United States is seeking a Staff Software Development Engineer in Test (SDET) specializing in Data Connectors and High-Scale Ingestion. You will design testing frameworks and benchmarking tools to validate multi-source data pipelines across AWS, Azure, and Kubernetes.

You will build automation suites for ingestion connectors (REST, gRPC, Kafka) and implement fault-injection with high-concurrency clusters.