Technical Support Engineer

Dataiku
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Director of Data Engineering & Support Operations

Senior Data Engineer

Data Engineer

Data Engineering Manager

Data Engineer

Data Engineer

At Dataiku, we're not just adapting to the AI revolution, we're leading it. Since our beginning in Paris in 2013, we've been pioneering the future of AI with a platform that makes data actionable and accessible. With over 1,000 teammates across 25 countries and backed by a renowned set of investors, we're the architects of Everyday AI, enabling data experts and domain experts to work together to build AI into their daily operations, from advanced analytics to Generative AI. 

What to know about the Dataiku Support Team

At Dataiku, the Support organization is a fully remote team focused on enabling our customers and helping them work through any technical issues or questions related to our Everyday AI Platform (DSS). We are a rapidly scaling and globally distributed team, with members spanning 10+ countries and across 3 major continents. Our focus is to take our growth to the next stage by building out an enterprise-grade global support function. 

How you’ll make an impact 

We are looking for an experienced technical support engineer who is comfortable working in a complex and dynamic environment and who can help contribute to the growth of our global support function as we continue to scale up our operations. As a Technical Support Engineer, you will help our EMEA and global customers solve their wide range of technical issues with Dataiku, such as installation, security, and integration with other big data technologies. You will also collaborate with various internal teams to solve and escalate customer issues as needed.

Some expected outcomes for this role 

Help EMEA and global customers solve their technical issues with Dataiku through a variety of communication channels

Communicate with our R&D team to solve complex issues and/or share feedback from our EMEA customers for future product improvement

Work with other customer-facing teams when escalating or rerouting issues to help ensure a proper and efficient / timely resolution

Document knowledge in the form of technical articles and contribute to knowledge bases or forums within specific areas of expertise

Occasionally wear multiple hats and help out with other activities in a fast-paced and dynamic startup team environment

What you’ll need to be successful 

At least 3 years of experience in a client-facing engineering or technical role, ideally involving a complex and rapidly evolving software/product

Experience with cloud platforms such as AWS, Azure, and GCP

Experience with Docker and Kubernetes

Collaborative and helpful mindset with a focus on always working as a team

A strong competency in technical problem solving with demonstrated experience performing advanced log analysis, debugging, and reproducing errors

Proficiency working with Unix-based operating systems

Experience with relational databases (or data warehouses like Snowflake) and SQL

Ability to read and write Python or R code

What will make you stand out

Experience with big data technologies, such as Hadoop or Spark 

Experience with authentication and authorization systems such as LDAP, SAML, and Kerberos

Experience with ML models and LLMs

What does the hiring process look like? #LI-Remote #LI-AN1

Initial call with a member of our Technical Recruiting team

Video call with the Technical Support Manager

Technical Assessment to show your skills (Home Test)

Debrief of your Tech Assessment with Support Team member

Final Interview with the VP Technical Support

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 . 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:Protect yourself from fraudulent recruitment activityDataiku 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

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.