Full-Time Pre-Sales Engineer - Cloud Data Warehousing

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.

Key Responsibilities:

1. 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
2. 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.
3. 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.
4. 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.
5. 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.

Qualifications:

• Technical Expertise:Strong experience with cloud data platforms such as Databricks, Snowflake, or similar solutions (Google BigQuery, AWS Redshift, etc.). In-depth knowledge of data engineering concepts, including data pipelines, ETL/ELT processes, and big data processing frameworks. Proven experience with AI/ML technologies, including model development, deployment, and integration into data workflows. Familiarity with data integration tools, real-time data processing, and advanced analytics pipelines. Experience with cloud environments (AWS, Azure, Google Cloud) and associated data services for storage, processing, and analytics.
• Sales & Customer Engagement:Proven ability to engage with senior technical and business stakeholders, demonstrating both technical expertise and business acumen. Experience in sales engineering, pre-sales support, or a similar technical sales role in the data, cloud, or AI/ML domain. Exceptional presentation, communication, and interpersonal skills, with the ability to explain complex technical concepts to a broad audience. Strong customer-focused mindset with the ability to articulate the business value of technical solutions.
• Experience & Education:Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience). 5+ years of experience in cloud data architecture, data engineering, AI/ML, or sales engineering. Hands-on experience with cloud data platforms (Databricks, Snowflake, etc.) and AI/ML tools (TensorFlow, PyTorch, etc.) is highly desirable.

Bonus Skills:Certifications in Databricks, Snowflake, AWS, Azure, or other relevant technologies. Familiarity with BI tools (Power BI, Tableau, Looker) and data visualization techniques. Experience working in an Agile development environment and with DevOps practices. Bonus: supply chain experience (if we want to focus/pitch supply chain projects in our analytics practice)

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