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# Staff Software Development Engineer in Test (Graph Database)

- **Company:** Veeam Software Corporation
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $250,400.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, Databases, Graph Database, Python (Programming Language), Online Analytical Processing, Neo4j, Software Engineering, Azure Data Factory, Backend, Kubernetes, Graphql, SDET
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_d3a35047bd14e32e7147022bf0ccf5f9

## About the Role

* 8+ years of experience in software development or test engineering using Java, Python, or Go
 * Expertise in graph technologies (Cypher, Gremlin, GraphQL, Neo4j, AWS Neptune) and complex relational/OLAP query validation
 * Strong cloud background across AWS and Azure data services, along with Kubernetes deployment orchestration
 * Experience verifying large-scale analytical databases and BI reporting backend engines

## Description

We are seeking a Staff Software Development Engineer in Test (SDET) focused on Graph Database Architectures and High-Volume Reporting Engines. You will lead the quality strategy for verifying complex graph traversals, indexing algorithms, multi-tenant analytics, and real-time visualization systems built across AWS and Azure cloud platforms., * Build automated test suites to verify node/edge relationship integrity, sub-graph query optimizations, and path traversal correctness (e.g., Neo4j, AWS Neptune, GraphQL) under concurrent workloads

 * Validate end-to-end data fidelity, dynamic aggregation accuracy, latency SLAs, and schema evolution across high-volume reporting layers
 * Design automated benchmarking platforms that measure query execution plans, indexing performance, and memory consumption under multi-gigabyte payload conditions
 * Leverage Kubernetes on AWS (EKS) and Azure (AKS) to spin up isolated, multi-tenant database clusters loaded with synthetic graph datasets for automated regression runs