A practical guide to coding interviews, system design rounds, take-home assignments, and pair programming sessions.
Technical interviews come in several forms, and the format you encounter will depend on the company, the role, and the seniority level. Understanding what each type involves lets you prepare with purpose rather than guessing what to expect.
The most common format. You are given an algorithmic or data-structure problem and asked to solve it in real time, either on a whiteboard, in a shared online editor such as CoderPad or HackerRank, or occasionally on paper. The interviewer watches you work and may ask follow-up questions about time complexity, edge cases, or alternative approaches. Sessions typically last 45–60 minutes, with one or two problems to solve.
More common at mid-level and senior roles. You are asked to design the architecture for a system — a URL shortener, a messaging platform, a rate limiter, or something specific to the company’s domain. There is no single correct answer. The interviewer is looking at how you break down a vague requirement into concrete components, how you reason about trade-offs, and whether you can communicate your thinking clearly.
The company sends you a problem to solve on your own time, usually with a deadline of two to seven days. These tend to be more realistic than whiteboard problems — build a small API, create a React component, write a data pipeline. The advantage is that you can work in your own environment without time pressure. The disadvantage is that they can consume significant unpaid time. In the UK, many candidates now push back on take-homes that exceed four hours, and some companies have responded by scoping them more tightly.
You work alongside an engineer from the company on a small problem or feature, usually in a real or near-real codebase. This format is increasingly popular among UK tech companies because it more closely resembles actual day-to-day work. The interviewer is evaluating how you collaborate, how you navigate unfamiliar code, and whether you ask useful questions.
Preparation for coding interviews is a skill in itself, distinct from being a good software developer. Many excellent engineers perform poorly in coding interviews simply because they have not practised the format. The good news is that targeted practice produces results quickly.
Understand core data structures and algorithms, but do not obsess. You should be comfortable with arrays, hash maps, linked lists, trees, graphs, stacks, queues, and common sorting and searching algorithms. You should understand Big O notation well enough to discuss time and space complexity. However, many UK companies — particularly startups and mid-sized firms — are moving away from LeetCode-style algorithmic puzzles in favour of more practical problems. Know the fundamentals, but do not spend six months grinding competitive programming problems unless you are targeting companies that explicitly use them.
Know your primary language inside out. Interviewers notice when you fumble with basic syntax, standard library functions, or language idioms. If you are interviewing in Python, you should know list comprehensions, dictionary methods, and common modules without looking them up. If you are using JavaScript, you should understand closures, promises, and array methods fluently. Depth in one language is more impressive than shallow knowledge of several.
Practise in the actual interview environment. If the company uses CoderPad, practise in CoderPad. If they use HackerRank, practise there. The experience of writing code without autocompletion, without your usual IDE shortcuts, and without being able to run tests freely is genuinely different. Many candidates lose time in interviews because they are fighting the environment rather than solving the problem.
Time-box your practice sessions. Give yourself 25–30 minutes per problem, which mirrors real interview conditions. If you cannot solve a problem in that window, read the solution, understand it, and move on. Spending three hours on a single problem builds persistence but not interview readiness. You need volume and pattern recognition more than deep struggle on individual questions.
System design interviews are less about knowing the right answer and more about demonstrating structured thinking. The interviewer gives you a deliberately vague prompt and watches how you navigate ambiguity.
Start with requirements. Before drawing a single box, clarify the scope. How many users does this system need to support? What are the most important features? Is consistency or availability more critical? Are there latency requirements? Asking these questions is not a sign of weakness — it is exactly what the interviewer wants to see. Engineers who dive straight into architecture without understanding the constraints are making assumptions they have not validated.
Draw the high-level architecture first. Sketch out the major components: clients, load balancers, application servers, databases, caches. Show how data flows through the system. Only after the interviewer agrees with your high-level approach should you drill into specific components. This top-down approach prevents you from spending thirty minutes on database schema design when the interviewer wanted to discuss caching strategy.
Discuss trade-offs explicitly. There is no single correct architecture for any system. When you choose a relational database over a document store, say why. When you introduce a message queue, explain what problem it solves and what complexity it adds. Interviewers are evaluating your ability to reason about trade-offs, not your ability to recite a textbook architecture. Mention scaling considerations, caching layers, database indexing strategies, and message queues where they are relevant, but only when you can explain why they are needed for the specific problem at hand.
Be honest about what you do not know. If you have never worked with a particular technology, say so. Then explain what you would expect it to do based on your understanding of similar systems. This is far more impressive than bluffing.
How you behave during the interview matters as much as whether you reach the correct solution. Interviewers are evaluating your process, not just your output.
Think aloud. Narrate your reasoning as you work. “I am considering using a hash map here because I need O(1) lookups” is infinitely more useful to the interviewer than silent typing followed by a finished solution. If your approach turns out to be wrong, the interviewer can redirect you. If you are silent, they cannot help.
Ask clarifying questions before you start coding. Can the input contain negative numbers? Is the list guaranteed to be sorted? Can there be duplicate values? These questions demonstrate that you think about edge cases before writing code, which is exactly what experienced engineers do in production.
Start with a brute force approach, then optimise. A working O(n²) solution is better than an incomplete O(n) solution. Get something correct first, verify it handles the basic cases, and then discuss how you would improve it. Many candidates fail because they aim for the optimal solution immediately and run out of time with nothing working.
Manage your time. If the interviewer tells you there are two parts to the question, do not spend forty minutes on part one. Solve the first part adequately, then move on. A complete but imperfect solution across both parts scores better than a perfect solution to only the first.
If you are stuck, say so. Describe what you have tried, what you think the obstacle is, and what approaches you are considering. Interviewers often give hints, but they can only do so if they understand where you are stuck. Sitting in silence for five minutes helps nobody.
Interviewers are evaluating your problem-solving process, communication skills, and how you handle ambiguity — not whether you memorised the optimal solution.
Understanding what interviewers are actually looking for can change how you prepare. Most technical interviews are scored across several dimensions, and the final answer is only one of them.
Code quality and readability. Even under time pressure, interviewers notice whether you use meaningful variable names, break logic into functions, and write code that another developer could understand. Sloppy code that works is a weaker signal than clean code that works.
Testing mindset. Do you consider edge cases without being prompted? Do you walk through your solution with a test input before declaring it finished? Do you ask about boundary conditions? Engineers who think about testing naturally are engineers who write reliable code in production.
How you respond to hints. When the interviewer suggests a different approach or points out an issue, do you listen and adapt, or do you double down on your original idea? The ability to incorporate feedback gracefully is a signal of how you will behave during code reviews and technical discussions with colleagues.
Collaboration and communication. Technical interviews are conversations, not examinations. The interviewer is imagining what it would be like to work with you every day. Can you explain your reasoning clearly? Do you listen to their input? Are you pleasant to interact with under pressure? These soft factors carry more weight than most candidates realise, particularly at companies where team fit is a significant hiring criterion.
Ultimately, the goal of a technical interview is not to prove that you know everything. It is to demonstrate that you can think clearly, communicate effectively, and write reasonable code under constraints — and that you would be someone your future colleagues would want to work alongside.
Prepare for your next technical interview with real questions: