Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

In Business Solutions, we are building apps that leverage Dataiku’s capabilities in data and AI, focused on key enterprise use cases that need their own, user-focused UI’s and flows. We do this for customers in verticals such as Manufacturing, Life Sciences and Finance, powering key processes within their business- and operating models. In short: our work truly is part of “everyday AI”!

How you’ll make an impact

• Build Innovative AI-Driven Applications: Design, develop, and deploy AI-powered applications that solve complex business problems, integrating Dataiku’s backend AI capabilities with user-centric, intuitive front-end interfaces.
• Work with Data Scientists and Industry Specialists: Collaborate with solutions engineers, data scientists, and industry experts to develop the best solutions for customers. Help define requirements and deliver state-of-the-art applications that meet user needs across different verticals such as finance, manufacturing, and life sciences.
• Empower Business Users: Create applications that allow expert users to work with large datasets and extract meaningful insights quickly and intuitively. Your goal is to bring complex data to life in the browser and simplify interactions with large-scale data sets.
• Drive Continuous Improvement: Take responsibility for the end-to-end lifecycle of applications—from PoC to production. Contribute to the maintenance and evolution of the tech stack and frameworks, and support new features and architecture improvements to ensure scalability and reliability.
• Collaborate Across Teams: Work closely with core teams to ensure high-quality, reusable components, provide best practices, and help make data scientists and business users autonomous in building solutions end-to-end.
• Contribute to Team Growth: Help mentor new team members, participate in interviews, and contribute to onboarding processes. Bring your expertise and enthusiasm to help grow a collaborative, inclusive, and innovative team culture.

What you’ll need to be successful 

• Full-Stack Development Experience: You have experience in full-stack software engineering, with experience taking an app from PoC to production. You are comfortable working across the stack—from the front-end user interface to the back-end infrastructure.
• Front-End Skills: Proficiency in modern reactive front-end frameworks like Vue.js (preferred), React, or Angular. You have a deep understanding of building user-centric, interactive web applications.
• Back-End Skills: Strong experience with backend development, especially with Python (FastAPI, Flask, etc.). You are familiar with RESTful API design and willing to adapt to Dataiku’s tech stack and best practices.
• Experience with Data-Intensive Applications: You understand the challenges of working with large datasets and designing high-performance, data-driven applications. Experience with analytics products or data platforms is a strong plus.
• Customer-Oriented Mindset: You have a strong focus on solving real-world problems for customers. You understand that building an effective product means diving deep into customer use cases, iterating based on feedback, and delivering the most relevant and efficient solutions.
• Curiosity: You are excited to learn, adapt, and take on new challenges. Whether it's discussing architecture, troubleshooting issues, or writing code, you are driven to make an impact and contribute to the team’s success.
• Tech Enthusiast: You’re genuinely passionate about AI and data-driven applications. You’re excited by the possibility of using cutting-edge AI technologies, like LLMs, to shape the future of business.

What does the hiring process look like?

• 45 min call with a Technical Recruiter
• Technical video interview with an Engineering Team Lead
• Take home assignment or Live Coding session
• 2 last interviews with VPs of Engineering

How you’ll make an impact

At Dataiku, our mission is to enable customers to bring large-scale data analytics and AI technologies into a centralized, easy-to-use platform. To support this mission, we are looking for an Infrastructure Engineer to help operate, maintain, and troubleshoot our internal and customer-facing infrastructure.

You will work closely with experienced infrastructure and platform engineers, contributing to the reliability and day-to-day operations of our systems. This role is hands-on and operationally focused, with a strong emphasis on UNIX/Linux systems and cloud infrastructure.

Our infrastructure primarily runs on AWS, with some components on Azure and GCP. The tooling environment includes Terraform, Ansible, Kubernetes, and Python, though deep expertise in all of these is not required at entry.

What you’ll work on

• Operate, maintain, and troubleshoot UNIX/Linux systems running in cloud environments
• Support and maintain existing configuration management and Infrastructure as Code setups
• Assist with the operation of cloud-based infrastructure, including virtual machines, networking components, and managed services
• Help monitor system health and performance, investigate alerts, and participate in incident response and root cause analysis
• Perform routine infrastructure updates and maintenance to ensure systems remain secure, reliable, and up to date
• Support Kubernetes clusters and containerized workloads, primarily from an operational and troubleshooting perspective
• Collaborate with senior engineers to improve automation, monitoring, and operational practices
• Document procedures, operational runbooks, and troubleshooting steps to improve team efficiency

What you need to be successful

• Experience working with UNIX/Linux systems, including hands-on troubleshooting and shell scripting
• Understanding of networking fundamentals (TCP/IP, DNS, routing, firewalls, load balancing) in cloud or data-center environments
• Basic experience operating infrastructure in a cloud environment (preferably AWS), including compute, networking, and monitoring services
• Basic scripting or development experience (e.g., Python)
• Clear communication skills and a collaborative, respectful approach to working with teammates
• Willingness to learn, ask questions, and grow technical depth over time

Nice to have

• Exposure to Infrastructure as Code tools such as Terraform
• Familiarity with at least one configuration management or automation tool (e.g., Ansible, Chef, Puppet, SaltStack)
• Familiarity with Kubernetes or container-based environments
• Experience with monitoring tools such as Grafana or similar platforms
• Ability to investigate incidents, follow runbooks, and escalate appropriately when needed
• Interest in automation and reliability, even if you have not yet designed large-scale systems yourself #LI-Hybrid #LI-FR1

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Berlin office or full remote from any part of Germany.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
  • Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
  • Collaborate with research teams on innovative machine learning experiments
  • Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring
    
    
• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our London office or full remote from any part of the UK.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Amsterdam office or full remote from any part of Netherlands.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
• Build tools to automate retraining, monitoring, and deployment of ML models
• Enhance collaboration features for ML stakeholders
• Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
  
  
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
• Optimize processing engines for scalability and latency
• Expand capabilities to support new databases and cloud platforms
• Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
  
  
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
• Develop customizable platforms for managing AI compliance and governance
• Simplify policy enforcement and integration across disparate systems
• Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45 min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote