Pre-Sales Engineer – Cloud Data Warehouse, Data Engineering & AI - US Based - Remote

Job Overview:

We are looking for a highly skilled and motivated Sales Engineer with deep expertise in cloud data warehousing, data engineering, and AI/ML to join our growing sales engineering team. In this client-facing role, you will collaborate with the sales team to present tailored, cutting-edge solutions that leverage platforms like Databricks and Snowflake for cloud data warehousing and AI/ML integration. You will be the bridge between business needs and technical solutions, helping customers navigate complex data challenges and drive impactful outcomes with data engineering and AI technologies.

Key Responsibilities:

Pre-Sales Support & Solution Design:

• Collaborate with the sales team to deeply understand customer business requirements and design scalable cloud data architectures using Databricks, Snowflake, and other cloud-based data platforms.
• Present tailored product demonstrations, Proof of Concepts (POCs), and architectural walkthroughs to showcase the capabilities of cloud data solutions and AI/ML integrations.
• Develop and deliver high-impact technical presentations and workshops on data engineering best practices, cloud data architecture, and AI-driven analytics.
• Assist with RFP/RFI responses, crafting technical solutions and aligning with customer objectives to win business.
• Facilitate data strategy workshops to roadmap client analytics priorities 
• Build scopes of work for data projects 

AI & Data Engineering Expertise:

• Work closely with customers to understand their data engineering workflows, including data pipelines, ETL processes, and data integration needs.
• Advise clients on the optimal design and implementation of data pipelines, automation strategies, and the integration of AI/ML models for real-time or batch processing.
• Assist clients in identifying key use cases for AI/ML, guiding them on how to integrate machine learning models into their data architecture for predictive analytics, anomaly detection, or automation.

Customer Engagement & Support:

• Act as a trusted advisor to customers, helping them to solve complex data and AI challenges while ensuring they realize the full potential of Databricks, Snowflake, and other cloud technologies.
• Develop strong, ongoing relationships with customers, providing continuous guidance on optimizing their data infrastructure and AI capabilities.
• Partner with customer success and support teams to ensure smooth implementation and ongoing customer satisfaction.

Collaboration & Knowledge Sharing:

• Work closely with Product Management, Engineering, and Data Science teams to understand product roadmaps, new feature releases, and customer feedback.
• Train and mentor internal sales teams on the latest advancements in cloud data warehousing, data engineering, and AI technologies.
• Stay up-to-date with emerging trends in AI, machine learning, cloud data platforms, and data engineering methodologies, and share that knowledge with the team and customers.

Technical Enablement & Best Practices:

• Build and maintain technical documentation, presentations, and other collateral to support customer engagement.
• Contribute to the creation of best practices, white papers, and technical case studies around the integration of cloud data warehouses and AI/ML technologies.
• Lead internal training sessions, webinars, and knowledge-sharing events to educate internal teams and customers on AI-driven data solutions.