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Automation Architect – Quality Engineering
Data Direct Networks
Francia
A distancia
EUR 60.000 - 80.000
Jornada completa
Hace 8 días

Descripción de la vacante

A leading data management company in Auvergne-Rhône-Alpes is seeking an Innovation-focused Automation Architect to enhance the quality engineering of their distributed storage platform. You will lead the design of an automation self-service platform, implement AI-driven testing techniques, and ensure high standards of code quality. The ideal candidate has expert-level Python skills, experience with distributed systems, and a strong command of CI/CD tools. This opportunity promises to significantly impact engineering efficiency in a challenging environment.

Responsabilidades

  • Take ownership of pytest-based automation framework.
  • Develop reusable Python libraries for testing.
  • Design automation as a self-service platform.
  • Create documentation and onboarding paths.
  • Implement AI-driven testing strategies.
  • Lead code reviews for automation submissions.
  • Architect automation for complex distributed systems.
  • Integrate performance testing into CI/CD pipelines.
  • Extend automation to chaos engineering.
  • Design high-efficiency automation across platforms.
  • Use telemetry for quality validation.
  • Mentor QE and Development engineers.

Conocimientos

Expert-Level Python
Distributed Systems
Linux & Storage Systems
Performance & Orchestration
CI/CD Expertise
Observability
AI/ML for QA
Scripting

Herramientas

pytest
Docker
Kubernetes
Grafana
Prometheus
ELK Stack
fio
IOR
Minio Warp
GitHub Actions
Bash
Descripción del empleo
Overview

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence.

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management.

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage.

Job Description

We\'re looking for a hands-on Automation Architect to lead the next generation of quality engineering for our distributed storage platform. This is a role for a true innovator, focused on writing world-class code and pioneering new approaches to testing using AI/ML and chaos engineering. You\'ll be the driving force behind designing automation as a self-service platform for all of engineering, focused on solving real problems, accelerating test execution, and removing friction across environments. If you thrive on solving complex problems and building tools that make engineering teams faster and smarter, this is your opportunity to make a massive impact.

What You\'ll Do
  • Architect & Own: You will take full ownership of our pytest-based automation framework, driving its architecture and evolution to set the new standard for quality at Infinia.
  • Create Reusable Tools: Develop robust and reusable Python libraries and pytest fixtures to streamline testing across our APIs, CLIs, and complex workload orchestration scenarios.
  • Build Automation as a Service: Design the framework as a self-service platform, creating a "paved road" that enables developers to easily write, run, and contribute to automation for their own features.
  • Drive Adoption: Create clear documentation, examples, and onboarding paths to evangelize automation best practices and drive adoption of the framework across the entire engineering organization.
  • Pioneer AI-Driven Testing: Research and implement modern testing strategies using lightweight AI/ML techniques (e.g., NumPy, SciPy, scikit-learn) to create more intelligent, adaptive, and realistic workloads for cluster, storage, and QoS validation.
  • Uphold Code & Product Quality: Champion high standards by leading code reviews for all automation submissions, from core framework enhancements to individual test cases, ensuring a high bar for quality and maintainability in the repository.
  • Test for Scale and Resilience: Architect and implement automation that validates complex distributed system behaviors, including clustering, service failover, and horizontal scaling.
  • Champion Resilience & Chaos Engineering: Extend automation beyond simple failure injection to embrace the principles of chaos engineering, proactively discovering systemic weaknesses.
  • Integrate Performance Testing: Seamlessly weave performance and stress testing into our CI/CD pipelines using tools like fio, IOR, Minio Warp, Mongoose and MLPerf to validate throughput, latency, and system resilience under pressure.
  • Scale with Modern Infrastructure: Design and deploy automation that runs with high efficiency and throughput across Kubernetes, Docker, hypervisors, and bare-metal systems, ensuring test execution scales seamlessly with development.
  • Drive Telemetry-Driven Quality: Integrate test results with our observability stack (Grafana, Prometheus, ELK) to move beyond simple pass/fail and validate quality using rich system telemetry.
  • Mentor & Lead: Act as a key technical leader and mentor for QE and Development engineers worldwide, elevating their skills in Python, pytest, and modern automation design patterns.
What You\'ll Bring

Technical Skills:

  • Expert-Level Python: Deep, hands-on mastery of Python, including pytest (fixtures, plugins, parametrization), asyncio, and building scalable frameworks.
  • Distributed Systems: A strong understanding of clustering, fault tolerance, and horizontal scaling principles. Experience with machine orchestration is highly desirable.
  • Linux & Storage Systems: Extensive experience with Linux (Ubuntu/RHEL) and a strong understanding of storage protocols like S3/Object, NVMe/iSCSI, and NFS/SMB.
  • Performance & Orchestration: Proven ability to integrate performance tools (fio, IOR, Minio Warp) and orchestrate tests within Docker and Kubernetes.
  • CI/CD Expertise: A strong command of Jenkins or GitHub Actions for building, maintaining, and troubleshooting complex automation pipelines.
  • Observability: Experience using Grafana, Prometheus, or the ELK Stack to analyze test results and system behavior.
  • AI/ML for QA (Preferred): Experience applying data science or machine learning techniques to solve testing problems. Familiarity with libraries like Pandas, NumPy, SciPy, and scikit-learn is a strong plus.
  • Scripting: Proficiency in Bash is a must. Bonus points for Go or C++ experience.

Leadership & Soft Skills:

  • A Builder\'s Mindset: You have a demonstrated history of writing and owning code, not just configuring off-the-shelf tools.
  • A Passion for Enablement: You are dedicated to building tools that other engineers find intuitive and powerful, and you are driven to help them succeed.
  • Commitment to Quality: You believe that rigorous code reviews are essential for building robust, maintainable automation and for sharing knowledge across the team.
  • Strategic Thinker: You can design a high-level automation strategy while also diving deep into the code to solve complex technical challenges.
  • Natural Mentor: You find satisfaction in teaching others and helping your colleagues grow their technical skills.
  • Excellent Communicator: You can clearly articulate complex technical ideas to both technical and non-technical stakeholders.
DDN

DDN has a very strong orientation towards these 4 characteristics and any successful employee will demonstrate these capabilities:

Self-Starter - Takes independent action to identify and solve problems. Seeks out relevant information needed to make decisions. Gets involved with new initiatives.

Success/Achievement Orientation - Delivers quality results consistently. Targets, achieves (or exceeds) measurable results. Sets challenging goals, focuses on critical priorities, and is accountable.

Problem Solving - Recognizes problems and responds with a systematic assessment that identifies and addresses cause of issue. Practical, realistic, and resourceful.

Innovative - Builds and improves key business processes that enhance the effectiveness of DDN. Generates new ideas, challenges the status quo, and solves problems creatively.

DataDirect Networks, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

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