Senior Software Engineer in Test - Anywhere Cloud

Business Area:

Engineering

Seniority Level:

Mid-Senior level

Job Description: 

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry.  Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

Team Overview
 

Ready to take cloud innovation to the next level? Join Cloudera’s Anywhere Cloud (AWC) team and help deliver a true “build your own pipeline, bring your own engine” experience, enabling data and AI workloads to run anywhere, without friction or vendor lock-in.

We take the best of the public cloud—cost efficiency, scalability, elasticity, and agility—and extend it to wherever data lives: public clouds, private data centers, and even the edge. Powered by Kubernetes, our hybrid architecture separates compute and storage, giving customers maximum flexibility and optimized infrastructure usage.
 

The Role

As a Senior Software Engineer in Test, specializing in Performance and Scale, you will own the execution, automated validation, and continuous performance testing of our highly distributed, multi-cluster control plane. You will implement robust performance test suites and test tools to validate AWC both as an application installed via Taikun and as a platform that orchestrates other clusters. You will be responsible for defining and running localized performance test suites to evaluate Zero-Trust security models, API-first contracts, and cross-cluster resource management under heavy loads.
 

Key Responsibilities

• Performance Framework Implementation & Scaling: Build, scale, and maintain comprehensive automated performance test suites capable of validating the core control plane, cluster provisioning, and multi-cluster engine deployments.

• Performance Baseline Ownership: Create and execute baseline test suites for measuring performance metrics and tracking regressions from release to release.

• Data Layer & Metastore Scale Validation: Implement high-concurrency test configurations for containerized metadata and storage layers to ensure they meet strict enterprise targets for vast table limits, high operations per second, and low-latency read operations.

• Profiling & Optimization Execution: Profile microservices performance, isolate infrastructure resource utilization bottlenecks (CPU, Memory, I/O), and work alongside backend core engineering to implement recommendations.

• Mentorship & Best Practices: Mentor junior and mid-level test engineers (IC1/IC2) on distributed systems performance engineering best practices and automation standards.

• Cross-Functional Execution: Collaborate closely with the Taikun (Kubernetes) and Foundational Services teams to integrate external components into the automated AWC performance test matrix.
   

Requirements

• Experience: 5+ years of professional experience as a Software Engineer in Test (SDET), Performance Engineer, or Quality Engineer within large-scale distributed systems or cloud-native environments.

• Performance Engineering Tools: Hands-on expertise building load generators and leveraging industry-standard benchmarking tools (e.g., k6, JMeter, Gatling, Locust) to validate throughput, latency, and concurrency limits across REST/gRPC interfaces.

• Kubernetes & Infrastructure: Strong proficiency with Kubernetes primitives, managing node/pod resource scaling limitations, and benchmarking storage IOPS profiles (e.g., Ceph, S3 object storage).

• Programming Languages: Strong coding proficiency in Python, Go (Golang), or Java to build robust test scripts, extend automation harnesses, and interact directly with distributed product APIs.

• Engine & Data Knowledge: Practical understanding of modern compute/streaming engine performance attributes (e.g., Spark tuning, Kafka throughput, Flink state backends) and open data lakehouse scale characteristics (e.g., Apache Iceberg).

• Observability Stack: Solid experience utilizing observability stacks (Prometheus, Grafana, OpenTelemetry) to actively monitor p95/p99 latencies, analyze system metrics, and isolate memory leaks during soak and endurance runs.

• AI Mindset: A proactive inclination towards adopting the latest AI productivity and AI-enabled test automation tools.

What you can expect from us:

• Generous PTO Policy 

• Support work life balance with Unplugged Days

• Flexible WFH Policy 

• Mental & Physical Wellness programs 

• Phone and Internet Reimbursement program 

• Access to Continued Career Development 

• Comprehensive Benefits and Competitive Packages 

• Paid Volunteer Time

• Employee Resource Groups

EEO/VEVRAA

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