Data architect interview questions
Use these suggested interview exercises to practice explaining assumptions, methods and validation. They are not a list of questions guaranteed to appear in an interview. The employer’s current requirements and assessment instructions take precedence.
Before you practice
Read the job description. Identify the responsibilities you would own. Ask about the assessment format, time limit, data, allowed tools and AI-assistance policy. Practice with public or synthetic data, and be ready to explain a step without relying on an assistant’s output.
How would you choose a data store?
Practice scenario: An application needs transactional updates and a separate analytical workload. Compare options and state what you would learn first.
What to explain: Ask about consistency, query patterns, data volume, recovery and operational capacity. Compare a small set of suitable options against those requirements. Explain where isolation or a separate analytical system is justified, and which assumptions would change the design.
How would you design a migration?
Practice scenario: A team wants to change the data model without losing reporting continuity. Outline a sequence and evidence for each step.
What to explain: Define source and target contracts, ownership, validation and a recovery plan. Use staged verification and reconciliations before consumers switch. Explain how you would handle incomplete mappings and changed definitions. A diagram alone does not prove that migration preserves meaning.
How would you govern access?
Practice scenario: Several teams need different views of the same customer dataset. Describe how permissions and definitions would be managed.
What to explain: Identify the permitted use and sensitive fields, choose access boundaries and name an owner for approval and review. Separate a shared metric definition from unrestricted data access. Record how changes are audited and how consumers can challenge an incorrect definition.
Review your answer
Check whether you defined the question, justified the method and proposed a way to verify the result. Include a failure case and a limitation. Our suggested rubric assesses reasoning and evidence; it is not an employer’s official scoring system.
Questions for the interviewer
- Which deliverable would I own, and who reviews it?
- What data-quality or operational problems does the team currently face?
- How do you assess success and support learning in this role?
Sources and next steps
Sources checked on October 2, 2026. Follow the linked documentation for current requirements.