Prepare from the job description
List every technology and concept in the job description and rate yourself on each. Spend most of your time on the core items rather than everything at once. A Java role will go deep on core Java, collections, multithreading, Spring Boot and SQL. A data analyst role will focus on SQL, statistics basics, Excel or Python and a BI tool.
- Core language concepts and common interview topics for your stack
- Databases and SQL: joins, indexing, window functions, transactions
- Tools on your resume: be ready to go deep on each one
- Basics of cloud, Git, CI/CD and testing for most developer roles
Know your projects deeply
Interviewers often spend half the round on your projects. Be ready to draw the architecture, explain why choices were made, what went wrong and what you would change. If something on your resume was mostly done by a teammate, be clear about your part.
Think out loud and clarify
Before answering a problem, restate it and ask about inputs, scale or edge cases. Explain your approach before coding or writing a query. If you get stuck, say what you are considering. Interviewers can guide you only when they hear your thinking.
- Ask: what is the expected input size? Are nulls possible?
- Start with a simple working approach, then optimise
- State trade offs: time versus space, consistency versus speed
When you do not know the answer
Do not bluff. Say you have not worked with it directly, then reason from what you do know or explain how you would find out. Honest reasoning is far better than a confident wrong answer that unravels under follow up questions.
Practise in realistic conditions
Use timed practice and speak your answers aloud. InterviewPlan AI mock interviews include technical questions by role with feedback, Coding Help supports problem practice, and the Interview Copilot supports technical interviews on platforms where the employer's rules allow assistance.