At Dataiku, we're not just adapting to the AIrevolution, we're leading it. Since our beginning in Paris in 2013,we've been pioneering the future of AI with a platform that makesdata actionable and accessible. With over 1,000 teammates across 25countries and backed by a renowned set of investors, we're thearchitects of Everyday AI, enabling data experts and domain expertsto work together to build AI into their daily operations, fromadvanced analytics to Generative AI. Why Engineering at Dataiku?Dataiku’s SaaS, cloud or on-premise deployed platform connects manyData Science technologies. Our technology stack reflects ourcommitment to quality and innovation. We integrate the best of dataand AI tech, selecting tools that truly enhance our product. Fromthe latest LLMs to our dedication to open source communities,you'll work with a dynamic range of technologies and contribute tothe collective knowledge of global tech innovators. What to knowabout the Field Engineering team As a Field Engineer, you’ll workwith customers at every stage of their relationship with Dataiku -from the initial evaluations to enterprise-wide deployments. Inthis role, you will help customers to design, build, validate, andrun their Data Science and AI Platforms. How you’ll make an impactThis role requires strong technical abilities, adaptability,inventiveness, and strong communication skills. Sometimes you willwork with clients on traditional big data technologies such as SQLdata warehouses, while at other times you will be helping them todiscover and implement the most cutting edge tools; Spark onKubernetes, cloud-based elastic compute engines, and GPUs. If youare interested in staying at the bleeding edge of big data and AIwhile maintaining a strong working knowledge of existing enterprisesystems, this will be a great fit for you. Some expected outcomesfor this role: 1. Understand customer requirements in terms ofscalability, availability and security and provide architecturerecommendations. 2. Deploy Dataiku in a large variety of technicalenvironments (SaaS, Kubernetes, Spark, Cloud or on-prem). 3.Automate operation, installation, and monitoring of the DataScience ecosystem components in our infrastructure stack. 4.Collaborate with Revenue and Customer teams to deliver a consistentexperience to our customers. 5. Drive technical success by being atrusted advisor to our customers and our internal account teams.What you need to be successful: 1. Professional experience with atleast one cloud based services (AWS, GCP or Azure). 2. Hands-onexperience with the Kubernetes ecosystem for setup, administration,troubleshooting and tuning. 3. Familiarity with Ansible or otherapplication deployment tools (Terraform, CloudFormation, etc). 4.Experience with cloud based Data Warehouses and Data Lakes(Snowflake, Databricks). 5. Some experience with Python. 6. Gritwhen faced with technical issues. 7. Comfort and confidence inclient-facing interactions. 8. Ability to work both pre and postsale. What will make you stand out: 1. Some knowledge in DataScience and/or machine learning. 2. Hands-on experience with Sparkecosystem for setup, administration, troubleshooting and tuning. 3.Experience with authentication and authorization systems like(A)AD, IAM, and LDAP. What does the hiring process look like? 1.Initial call with a member of our Technical Recruiting team. 2.Video call with the Field Engineer Hiring Manager. 3. TechnicalAssessment to show your skills (Home Test). 4. Debrief of your TechAssessment with Field Engineer Team members. 5. Final Interviewwith the VP Field Engineering. What are you waiting for! AtDataiku, you'll be part of a journey to shape the ever-evolvingworld of AI. We're not just building a product; we're crafting thefuture of AI. If you're ready to make a significant impact in acompany that values innovation, collaboration, and your personalgrowth, we can't wait to welcome you to Dataiku!#J-18808-Ljbffr
