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# Staff Software Development Engineer

- **Company:** Veeam Software Corporation
- **Location:** San Jose, United States
- **Experience:** Expert
- **Salary:** $250,400.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Build Automation, Microsoft Azure, C++ (Programming Language), Python (Programming Language), Load Testing, Queueing Systems, RabbitMQ, Software Engineering, Data Streaming, WebSocket, Azure Service Bus, Kubernetes, Apache Kafka, Restful APIs, Amazon Simple Queue Service (SQS), Grpc, SDET, Golang
- **Published:** September 16, 2026
- **Apply:** https://startup.jobs/staff-software-development-engineer-in-test-veeam-software-10082984

## About the Role

* 8+ years of software engineering/SDET experience in C++, Java, Go, or Python
 * Deep experience in testing streaming architectures (Kafka, Event Hubs), queueing systems, and API protocols (gRPC, WebSockets, REST)
 * Hands-on proficiency with AWS, Azure, and Kubernetes (Helm, custom controllers, or K8s operators)
 * Proven track record building custom distributed load-generation tools (e.g., Locust, k6, custom Go/Java engines)

#LI-AA3

## Description

We are seeking a Staff Software Development Engineer in Test (SDET) specializing in Data Connectors & High-Scale Ingestion. In this role, you will be the technical authority responsible for designing testing frameworks and benchmarking tools that validate multi-source data integration pipelines processing petabyte-scale throughput across AWS, Azure, and Kubernetes., * Design and execute scalable performance, backpressure, and stress-testing harnesses for ingestion connectors (REST, gRPC, CDC, Kafka, RabbitMQ)

 * Build automation suites across AWS (S3, SQS, Kinesis, EKS) and Azure (Event Hubs, Blob, AKS) to test real-world connector data flows under degraded network conditions and extreme concurrency
 * Implement automated fault-injection pipelines (simulating schema drift, network partitions, rate limits, and authentication failures) to guarantee zero-data-loss execution
 * Utilize Kubernetes to dynamically orchestrate transient, high-concurrency test clusters and mock target endpoints at scale


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