Senior Field Engineer

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube . Why Engineering at Dataiku? Dataiku’s SaaS, cloud or on-premise deployed platform connects many Data Science technologies. 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. What to know about the Field Engineering team As a Field Engineer, you’ll work with customers at every stage of their relationship with Dataiku - from the initial evaluations to enterprise-wide deployments. In this role, you will help customers to design, build, validate, and run their Data Science and AI Platforms. How you’ll make an impact This role requires strong technical abilities, adaptability, inventiveness, and strong communication skills. Sometimes you will work with clients on traditional big data technologies such as SQL data warehouses, while at other times you will be helping them to discover and implement the most cutting edge tools; Spark on Kubernetes, cloud-based elastic compute engines, and GPUs. If you are interested in staying at the bleeding edge of big data and AI while maintaining a strong working knowledge of existing enterprise systems, this will be a great fit for you. Some expected outcomes for this role: Understand customer requirements in terms of scalability, availability and security and provide architecture recommendations Deploy Dataiku in a large variety of technical environments (SaaS, Kubernetes, Spark, Cloud or on-prem) Automate operation, installation, and monitoring of the Data Science ecosystem components in our infrastructure stack Collaborate with Revenue and Customer teams to deliver a consistent experience to our customers Drive technical success by being a trusted advisor to our customers and our internal account teams What you need to be successful: Professional experience with at least one cloud based services (AWS, GCP or Azure) Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting and tuning Familiarity with Ansible or other application deployment tools (Terraform, CloudFormation, etc) Experience with cloud based Data Warehouses and Data Lakes (Snowflake, Databricks) Some experience with Python Grit when faced with technical issues Comfort and confidence in client-facing interactions Ability to work both pre and post sale What will make you stand out: Some knowledge in Data Science and/or machine learning Linux system administration experience Hands-on experience with Spark ecosystem for setup, administration, troubleshooting and tuning Experience with authentication and authorization systems like(A)AD, IAM, and LDAP What does the hiring process look like? #LI-Hybrid #LI-AN1 Initial call with a member of our Technical Recruiting team Video call with the Field Engineer Hiring Manager Technical Assessment to show your skills (Home Test) Debrief of your Tech Assessment with Field Engineer Team members Final Interview with the Sr Director Field Engineering What ... (truncated, view full listing at source)