Field Engineer

Description:

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