Technical Account Manager

How you'll make an impact

• Collaborate with the customer and the internal account team to jointly identify short and long-term priorities and develop the associated engagement plan
• Manage project milestones in partnership with Customer Success Managers and clients, contribute to deliverables, provide regular status updates and proactively identify and mitigate issues and risks
• Serve as a central point for client technical information and contribute to the account strategy alongside the broader account team
• Support the growth and effectiveness of the Field Engineering team through documentation, process improvements, and knowledge sharing
• Act as the primary technical advisor for client teams, providing guidance and hands-on support across a range of areas, including:
  
  • Dataiku platform architecture and deployment
  • Platform operations and upgrades
  • Best practices for platform usage
  • Security, data management, and compute resources
  • ML-Ops, monitoring, and scaling strategies
• Assist clients in integrating the product into their systems and troubleshoot technical challenges
• Capture client feedback and feature requests to inform the Product and Engineering teams
• Advise client tech leaders on complementary technologies and long-term technical strategy.
• Explore and support advanced use cases involving Dataiku, such as edge computing, deep learning, and MLOps

What you'll need to be successful

• 7+ years of experience in a customer-facing technical role
• Strong communication and client relationship skills
• Experience supporting both pre- and post-sales engagements
• Proficiency in Linux system administration, including networking
• Experience with identity and access management tools (e.g., LDAP, Kerberos, Active Directory, IAM)
• Hands-on experience with cloud platforms (AWS, Azure, GCP)
• Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting and tuning
• Familiarity with the Hadoop and/or Spark ecosystems

How you'll stand out

• Experience with Python
• Data-Science knowledge
• Basic knowledge of Java
• Familiarity with ML-Ops practices and tools