Data and Artificial Intelligence Concepts Questions

Core data engineering and analytics concepts combined with artificial intelligence and machine learning fundamentals relevant to sales engineering. Topics include data modeling, data warehouse and data lake trade offs, batch versus real time processing, streaming and event driven pipelines, extract transform load and extract load transform approaches, analytics and reporting patterns, key performance indicators and metric design, and how these decisions affect latency cost and accuracy. For machine learning candidates should be able to explain model training validation and inference, feature engineering, model deployment and monitoring, machine learning operations and governance, and how to translate model capabilities into business impact for customers. Interviewers also assess the candidate's ability to frame technical trade offs and risks in customer friendly terms and to build simple outcome oriented narratives and metrics.