Dataiku is The Universal AI Platform™, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents. Providing no-, low-, and full-code capabilities, Dataiku meets teams where they are today, allowing them to begin building with AI using their existing skills and knowledge.

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 fullremote 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

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

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

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