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Salary: USD 250,400 - 465,100 / annual
Veeam, the Data and AI Trust Company, is seeking a Staff Software Development Engineer in Test (SDET) to lead quality strategy for graph database architectures and high-volume reporting engines. You will own automated testing for complex graph traversals, indexing algorithms, multi-tenant analytics, and real-time visualization systems deployed across AWS and Azure cloud platforms.
Key responsibilities include:
- Building automated test suites to verify node/edge relationship integrity, sub-graph query optimizations, and path traversal correctness (Neo4j, AWS Neptune, GraphQL) under concurrent workloads
- Validating end-to-end data fidelity, dynamic aggregation accuracy, latency SLAs, and schema evolution across high-volume reporting layers
- Designing automated benchmarking platforms that measure query execution plans, indexing performance, and memory consumption under multi-gigabyte payload conditions
- Leveraging Kubernetes on AWS (EKS) and Azure (AKS) to spin up isolated, multi-tenant database clusters loaded with synthetic graph datasets for automated regression runs
Veeam protects over 550,000 customers worldwide and is headquartered in Seattle with offices in 30+ countries. The company is built for the convergence of identity, data, security, and AI risk.
Benefits include unlimited paid time off, 12 paid holidays plus 4 VeeaMe Days for self-care, 24 paid volunteer hours annually, paid parental leave (8 weeks standard, 16 weeks for birthing parents), medical/dental/vision coverage from day one, mental health support via EAP, 401(k) with company match, fertility/adoption/surrogacy support, 24/7 virtual veterinary care, legal services, and access to learning platforms (LinkedIn Learning, O'Reilly).
Requirements:
- 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
