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.
As enterprises worldwide become more and more invested in the cloud, Dataiku looks to expand its services and offerings to adapt to rapidly shifting customer needs. Dataiku brings together Large-scale data analytics and AI technologies into a unique and easy-to-use platform. It allows data scientists to process data with SQL databases, Spark, and Kubernetes with user-friendly visual interfaces or code.
To help us fulfill this mission, we are looking for a talented full-stack software engineer to work on the Data analytics part of Dataiku and other core features of the platform.
Our current technical stack is based on a mix of Java, Javascript and Python.
This position is either onsite from Paris, London, Berlin and Amsterdam or remote from these countries.
How you’ll make an impact:
(Note: this is a Software Engineer position, focused on developing Dataiku's features and capabilities. We have separate positions open for Data Engineers, Data Scientist and Data Analyst)
The mission of the Self-service Analytics teams is to maintain and improve the core features of Dataiku that are dedicated to Business Analysts & Developers, such as:
- Data integration: this includes reading from and writing to Snowflake, BigQuery, Redshift, Azure Synapse, flat files on S3 (CSV, Parquet, Excel, …)
- Data preparation & transformation through graphical UI, code or ChatGPT-like inputs, using the latest processing engines: Spark on K8s, SQL with UDFs, Snowpark, etc.
- Data catalog with automated quality assessment
- Jupyter notebooks & SQL workbench
- Help and onboarding experience
- Automation & public REST APIs
Some expected outcomes for this role:
- Add new ways to clean up data using Large Language Models such as ChatGPT
- Optimize our layout engine to be able to render complex workflows of 1000 datasets faster
- Support new databases capabilities to read/write or process data faster
- Improve our help system to make it smarter
- Strengthen our git support, including automatic and graphical merge conflicts resolutions
- Add autocomplete to our SQL workbench supporting a wide range of databases
What you need to be successful:
- You have experience in software development and are interested in data processing
- You are "customer-oriented" you want to understand how the product is used and solve actual customer problems
- You know, Data science is 80% preparing data and 20% complaining about preparing data
- You are curious about working 'under the hood' and want to learn how things are built
- You have firsthand experience (either professional or personal) in building a real product
- You don't hesitate to ask questions when you don't know, and treat your colleagues with respect, kindness, and honesty
What does the hiring process look like?
- Initial call with a member of our Technical Recruiting team
- Video call with an Engineering Team Lead
- Technical Assessment to show your skills (Home Test or Live Coding)
- Debrief of your Tech Assessment with Engineering Team member
- Final Interview with a VP Engineering #LI-Hybrid
