How do you answer data engineering interview questions?

3 Solve problems creatively

Data engineering is not only about technical skills, but also about problem-solving skills. You should be able to approach data engineering problems creatively, and come up with efficient and scalable solutions. You should also be able to communicate your thought process and reasoning clearly, and justify your choices and trade-offs. You should also be ready to handle unexpected scenarios and edge cases, and adapt your solutions accordingly. You should also be open to feedback and suggestions, and show your willingness to learn and improve.

4 Understand the big picture

Data engineering is not an isolated function, but a part of a larger data ecosystem that involves data science, analytics, machine learning, and business intelligence. You should be able to understand the big picture of how data engineering supports and enables these functions, and how they work together to deliver value and insights. You should also be aware of the current trends and best practices in data engineering, and how they affect the data landscape and the data-driven culture. You should also be able to identify the opportunities and challenges that data engineering faces, and how you can contribute to the growth and innovation of the field.

5 Be curious and enthusiastic

Data engineering is a dynamic and evolving field that requires constant learning and experimentation. You should be curious and enthusiastic about data engineering, and show your passion and interest in the field. You should also be proactive and self-motivated, and seek out new knowledge and skills that can enhance your data engineering capabilities. You should also be humble and respectful, and acknowledge your strengths and weaknesses, and your areas of improvement. You should also be collaborative and supportive, and share your ideas and insights with others, and learn from their feedback and experiences.