NTT DATA Data Engineer Interview Guide

When discussing a technical challenge, start by clearly outlining the context and the specific issue you encountered. For example, you might describe a scenario where you had to optimize a slow-running SQL query in a data pipeline. Detail the approach you took: first, analyzing the query's performance metrics, then identifying bottlenecks, and finally applying best practices like indexing or query refactoring. Conclude with the results of your actions, such as reduced processing time or improved data accuracy, and reflect on what you learned from the experience.

In your response, describe a specific project where you had to balance technical requirements with the needs of various stakeholders, such as product managers, data scientists, or executives. Highlight how you facilitated communication, perhaps through regular meetings or updates, and how you gathered requirements to inform your technical decisions. Discuss any challenges, such as differing priorities, and how you navigated these to achieve a successful outcome, such as delivering a data solution that satisfied both technical standards and business objectives.

When answering this question, emphasize your proactive learning strategies. For instance, you could explain how you utilized online courses, documentation, or community forums to get up to speed on a new technology like AWS services or Snowflake. Describe a specific project where this learning was critical, detailing how your new skills contributed to the project's success, such as improving data processing efficiency or enabling new functionalities that were previously not possible.