In this project walk-through, visualize a table as a graph network to get insights about complex connected data — the Game of Thrones characters.
Engineering at Dataiku
A look into how the R&D team works at Dataiku and what makes it special. TLDR: We prioritize quality of product and people's lives over deadlines.See open positions
We Are Building the Future of Working With AI
“If you don’t know where you want to go, then it doesn’t matter which path you take.”
— Alice in Wonderland
Dataiku’s story began in Paris in 2013 with a forward-thinking team of four entrepreneurs convinced that in order to succeed in the world’s rapidly evolving ecosystem, organizations — no matter their industry or size — must use data to continuously innovate. Our CEO Florian Douetteau and our CTO Clément Stenac, both co-founders, are experienced developers who believe great products solve complex problems.
We Work Together to Achieve our Common Goal
“I have always believed helping your fellow man is profitable in every sense, personally and bottom-line.”
— Michael Corleone, The Godfather
At Dataiku we all do “product first” — our developers don’t do “code first,” designers don’t do “design first,” and QA don’t do “tests first.” We all strive to achieve the best possible outcome for the product while also working together and fostering healthy teams.
We develop best-in-class products
Our software engineers (split into eight teams with dedicated scopes like ML, data viz, architecture, etc.), software engineers in test, product managers, and UX designers — all based out of Europe — work together to build the best Enterprise AI product.
We help our users
Our field engineers, architects, and technical support engineers — with the support of sales and customer success teams — help customers from all around the world, whether it’s with installation, training, or answering day-to-day questions.
We prepare for what’s next
Research scientists from The Lab investigate emerging AI & ML topics, build prototypes, write publications, and help prepare the future of our products. The Incubator team unveils new usages and explores promising product ideas.
Backend and Frontend
AI & Machine Learning
We Value Simple Over Shiny and Efficient Over Trendy
“It is not our abilities that show what we truly are… it is our choices.”
— Albus Dumbledore, Harry Potter & the Chamber of Secrets
Our tech stack (made up of the hottest data and AI tech, including Spark, Kubernetes, deep learning, and more) reflects who we are: a fast-growing company committed to integrating with the latest and greatest — when it makes sense — to provide the best product for our customers. Our backend is mainly written in Java but also includes some Python and bits of Scala and R. Our frontend is based on AngularJS, Angular and also makes vast usage of d3.js for interactive charts.
A Word About Open-source
You can think of our product as a control room for the more than 30 open-source tools with which the platform integrates. Most of our in-house plugins are also open source (Apache License). As a team, we contribute to major projects including:
Dataiku Lab is the author and maintainer of this Python package designed to perform and monitor active learning experiments, leveraging various query sampling methods and metrics.
We are part of the first consortium of corporate sponsors who support the development of this flagship machine learning library.
We Care About People and Quality More Than Deadlines and Delivery
“All we have to decide is what to do with the time that is given us.”
— Gandalf, the Lord of The Rings
Meet Some of the Team
Software Engineer in Test
Senior Research Scientist
We Are Agile in Our Own Way to Maximize Autonomy & Flexibility
“No need to report to him until we have something to report!”
— Nute Gunray, Star Wars: Episode I — The Phantom Menace
This is how we work everyday, and the Hackaiku week (an internal event held every year) is a good representation of this. The only rule is “do whatever you want” — results include rebuilding our Jenkins pipelines, writing a VS Code extension for Dataiku, or detecting and warning users of common errors in ML pipelines.
Pragmatism and flexibility are our driving principles. Rather than rigorously following a pre-established development methodology, we evolved our own based on existing ones, agile principles, and a number of practical issues we have observed in the past. We encourage all teams to adopt this process (but also let them customize it to their needs).
We avoid silos: People can easily express their desire to work on specific projects, and we encourage everyone to explore different technologies and aspects of the product.
We are autonomous: We trust our engineers and expect them to find their way through the code base by themselves as much as possible. This being said, we are always here to help each other as we don’t see the value of “getting stuck.” With this comes a lot of leverage (as well as responsibility) for technical choices.
We are impactful: At Dataiku, no matter your role, you are allowed to suggest, try out new things, and fail. As engineers, we not only have a say in how we do things but also in what we do.
Our View on Hot Topics
Four main principles guide our engineering hiring — here’s a look at them.
In this article from a Dataiku QA engineer, discover what QA can do and why they can't improve the quality of an application alone.
Hear from a Dataiku engineer on his key learnings from his mentorship experience with a senior Google engineer
How Dataiku Sandboxes Java to Avoid Heaps of Garbage
Learn how Dataiku DSS uses multiple JVMs to sandbox dangerous operations and survive OutOfMemory exceptions.
In this interview with 50inTech, Arnaud Pichery, VP Engineering at Dataiku, explains how he fights against gender inequality in tech.
Learn more about Dataiku's learning culture with our Tech Enablement Director Harizo.
Watch this Tech.Rocks meetup replay to hear Dataiku's CTO and co-founder Clément Stenac explain what our tech culture is about and how we keep it alive as we grow.