Staff Engineering In Test

We are seeking a highly skilled and technically strong Staff Engineer in Test to lead system level quality engineering efforts for Networking, security and other enterprise readiness aspects of DDN’s Ecosystem (Primarily for Hadoop Ecosystem).

In this role, you will be a senior technical QE responsible for planning and implementing test strategies and test infrastructures to ensure correctness, stability, performance, and resilience of DDN Ecosystem architecture. You will work across core subsystems-including the I/O path, memory management, networking stack, scheduling layers, multi-tenant services, and NVMe-backed storage. patterns-to ensure platform quality at scale. This is a hands-on, high-impact IC role for someone who can solve hard problems, automate at scale, leverage AI to improve velocity and elevate quality engineering across the organization.

Key Responsibilities:

• Quality Engineering & System Validation

• Design detailed test strategies and validation plans for networking and security features for distributed system

• Create scalable, automated test suites that validate Hadoop components for multi-tenant behavior, concurrency, data consistency, and system-level performance.

Automation Frameworks & Tooling

• Build and maintain robust automation using tools such as Hadoop benchmarks and container-based environments leveraging Docker, Jenkins, Kubernetes.

• Develop reusable automation templates, harnesses, and utilities to accelerate test creation and reduce engineering overhead.

Performance, Reliability & Scale Testing

• Construct and execute performance tests covering I/O throughput, system latency, NVMe access patterns, concurrency limits, and long-running workload stability.

• Use advanced tools (profilers, fuzzers, failure-injection frameworks, trace analyzers) to uncover issues in distributed workflows.

• Analyze CPU, memory, disk, and network utilization to diagnose performance bottlenecks and identify regression risks.

Cross-Functional Quality Leadership

• Work closely with architects, developers, release engineering, DevOps, and customer engineering to drive quality-first design decisions.

• Participate in feature design reviews, ensuring testability, observability, and resilience are built into system components.

• Lead root cause analysis (RCA) for complex issues and propose long-term improvements to engineering practices and platform stability.

Documentation & Quality Standards

• Produce clear, detailed test plans, automation guides, design-review feedback, and quality metrics reports.

• Contribute to the development and maintenance of internal QA standards, best practices, and. onboarding materials.

Required Qualifications

• 10+ years of experience in software quality engineering, with strong focus on distributed systems, system-level testing, or infrastructure platforms.

• Hands-on expertise in test automation using Python, Bash, and modern CI/CD tooling (Git, Jenkins, etc.).

• Strong understanding of: Distributed concurrency, File systems and I/O stack behavior, Storage performance analysis (NVMe, SPDK), Networking, tracing, and system observability

• Experience with large-scale performance testing, stress testing, and reliability validation.

• Demonstrated skill in diagnosing complex system issues across logs, traces, network captures, and profiling tools.

• Experience in Hadoop products preferred.

Preferred Qualifications

• Experience validating large-scale data platforms, storage engines, or distributed scheduling systems.

• Experience with AI technologies in context of quality engineering, such as issue triaging, test generation, automation.

• Familiarity with observability technologies such as OpenTelemetry, Grafana, Prometheus.

• Background in compliance or security testing (e.g., access control, backup/restore workflows, Section 508/HIPAA/PCI).

• Contributions to open-source test frameworks or distributed systems validation tools.