Sales Engineer

About Nexus

NexusOne is the converged data platform for the AI era. Composable by design, built on an open-source foundation, and AI-native from the ground up, NexusOne enables enterprises to bring their existing stack along while giving AI agents full context across the estate.

Responsibilities

• Work closely with Sales and Customer Success teams to articulate NX1 capabilities/differentiators, define solution options/benefits, and identify modernization opportunities for client-specific workloads
• Propose solution architecture and articulate benefits of NX1 for complex data-driven workloads
• Oversee initial customer onboarding ensuring automation, repeatability, and standardization across customer base
• Act as a key product stakeholder contributing to the product roadmap, prioritization, and architecture definition
• Work closely with NX1 Product and Architecture team to define, design, and implement new Control Plane product features and entitlements
• Contribute to NX1 and industry thought leadership and marketing content
• Cultivate a culture of innovation and continuous improvement
• Provide technical guidance and support to internal stakeholders on data analytics tools and best practices
• Stay updated with industry trends and emerging technologies in data analytics and open-source tools
• Develop standards, patterns, best practices, and formal training (boot camps) for internal engineers and client-facing delivery teams

Qualifications

• A minimum of 8 years of experience as a Solution Architect and 3 years as a Sales Engineer working with enterprise customers
• Proven track record supporting the technology sales processes with the ability to articulate business benefits to non-technical stakeholders
• Deep knowledge of open-source and proprietary modern data technologies, including Iceberg, Spark, Nifi, Jupyter Notebooks, Cloudera, Databricks, Kubeflow, MLFlow, Kafka, Debezium, etc.
• Experience designing/building solutions across major cloud platforms (AWS, Azure, and GCP) using Kubernetes, Terraform, and CI/CD principles
• Proven experience architecting data pipelines and data infrastructure to support AI and ML at scale
• Hands-on experience with programming languages, including Python, Java, Scala, GO, SQL, etc.