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Infrastructure Engineer

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Remote from
France
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
11 Nov 2026
Listing views
82
Application actions
4
Application toolkit

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AI Summary

The role, at a glance.

Dataiku seeks an Infrastructure Engineer to design, deploy, and operate internal data platforms and production environments for web services. The role combines infrastructure-as-code, managed Kubernetes, cloud networking and compute, Linux troubleshooting, and Python automation. The engineer will also contribute to product features involving cloud services and Linux integration while maintaining secure, reliable, scalable workloads. This is a collaborative infrastructure role supporting multiple technical teams and mission-critical AI platform deployments.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe position requires broad, hands-on expertise across cloud platforms, Kubernetes, Terraform, Linux internals, networking, and production operations. Diagnosing complex root causes and designing infrastructure used by multiple teams increases both technical depth and operational responsibility.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$145,000
US market range$115k–$180k
AI insightNo salary was disclosed in the posting. This is a US-market estimate for a mid-to-senior Infrastructure/DevOps Engineer with Kubernetes, Terraform, cloud, networking, Python, and Linux systems expertise; actual compensation in France may differ substantially.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a production Kubernetes platform for several internal web services?

I would begin with workload, availability, security, and data requirements, then define separate environments and namespaces with least-privilege RBAC. I would automate cluster and supporting cloud resources through Terraform, establish CI/CD deployment standards, configure ingress, secrets management, observability, autoscaling, backups, and network policies, and validate the design through failure testing and operational runbooks.

Describe your approach to troubleshooting a difficult Linux performance issue in production.

I first establish impact, scope, and recent changes while protecting service availability. I use system and application metrics, logs, process inspection, resource tools such as top, vmstat, iostat, and ss, plus kernel or network diagnostics as needed to isolate CPU, memory, disk, network, or application causes. I mitigate safely, confirm the root cause with evidence, and document preventive monitoring or configuration changes.

How have you used Terraform to make infrastructure delivery safer and more repeatable?

I organize reusable modules, environment-specific variables, remote state with locking, peer-reviewed plans, and CI checks for formatting, validation, policy, and security. Changes are applied through controlled pipelines rather than manually, with clear ownership of state and a rollback or remediation approach for high-risk resources.

What factors would you consider when selecting managed services across AWS, Azure, or GCP?

I would assess reliability requirements, operational overhead, security and identity integration, networking constraints, data residency, cost, portability, observability, and service limits. I would favor managed services when they reduce undifferentiated operational work without compromising required control, then document trade-offs and validate them with a proof of concept.

How do you collaborate effectively with application engineers when defining infrastructure solutions?

I translate platform constraints into practical developer-facing standards, gather application requirements early, and provide documented templates, self-service tooling, and clear escalation paths. I use design reviews and shared observability to make trade-offs visible, helping teams deliver safely without treating infrastructure as a separate silo.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack – empowering organizations to run AI across multi-vendor environments with centralized governance.

The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog, LinkedIn, X, and YouTube.

The Platforms Infrastructure team is seeking a driven individual to join us in addressing our evolving infrastructure challenges. At Dataiku, our mission is to architect, deploy, and maintain robust data platforms centered around our core product. We also provide industrialization and production configurations for mission-critical web services.

As domain experts, we proactively develop and disseminate reference infrastructure, best practices, knowledge, and tooling across all technical teams at Dataiku. This role encompasses a broad spectrum of responsibilities, from leveraging high-level managed services at hyperscalers to performing in-depth, low-level Linux debugging.

As a key contributor to the deployment of our core product, the team actively participates in development initiatives related to infrastructure and Linux system interactions.

We foster a collaborative environment and seek a like-minded individual to engage in highly collaborative projects. Effective communication skills are essential for interacting with diverse teams throughout the company.

This position is based in Paris and may be considered for remote work.

Your responsibilities:

  • Design, deploy, and manage our core product based internal data platforms.
  • Design, deploy, and configure production environments for multiple web services.
  • Collaborate with teams to architect technical solutions, and subsequently deploy and manage those solutions.
  • Develop core product features around cloud services and Linux integration.
  • Guarantee optimal service capacity and robust security for all running workloads and services.

The role might be a good fit if you have:

  • Proficiency in infrastructure automation using tools such as Terraform.
  • Expertise in container technologies and managed Kubernetes clusters.
  • Advanced scripting skills in Python.
  • Field experience with Linux operating systems and low-level system troubleshooting
  • Practical experience in networking and compute within a major cloud provider (AWS, Azure, or GCP).
  • Demonstrated resilience in resolving complex technical challenges, with a relentless pursuit of root cause analysis.

Bonus point for any of these:

  • Experience in implementing authentication and authorization systems, including LDAP, SAML, and OAuth2.
  • Experience with configuration management tools as Ansible, Puppet or Chef.
  • Knowledge of additional programming languages, particularly Go, considered a strong asset.
  • Experience in networking and compute across multiple cloud providers (AWS, Azure, or GCP).

What are you waiting for!

At Dataiku, you’ll be part of a journey to shape the ever-evolving world of AI. We’re not just building a product; we’re crafting the future of AI. If you’re ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can’t wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page.

Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com


Protect yourself from fraudulent recruitment activity

Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.

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