A system design interview tests your ability to architect large-scale, real-world systems. You are given an open-ended problem such as designing a URL shortener, chat app, or ticket booking platform, and you are expected to gather requirements, estimate scale, propose a high-level architecture using load balancers, caches, databases, and message queues, and justify your trade-offs. In India, it is a standard round for mid and senior software engineer roles at product companies, and even many fresher hiring processes now include a basic design round.

The classics repeat across companies: design a URL shortener, design a chat application like WhatsApp, design a social media feed, design BookMyShow or a ticket booking system, design a food delivery app, design a rate limiter, design a notification system, and design a scalable file storage service. It is smarter to deeply master 12–15 of these problems, including scaling, caching, sharding, and consistency trade-offs, than to skim 50 superficially. Interviewers reward depth and clear reasoning, not the number of designs you have memorized.

Work in this order: first build fundamentals such as scalability, latency vs throughput, CAP theorem, load balancing, caching, indexing, sharding, and replication; then study standard architectures; then practice 10–15 problems out loud within 35–45 minutes each. Most candidates fail because they read solutions passively instead of designing and speaking under time pressure. If you are stuck or short on time, a 1:1 deep dive into system design with someone who has built such systems, like Gaurav Raj, a Principal Engineer 2 with 14+ years in distributed systems, can compress months of self-study into weeks.

Pick one classic problem every week and design it end to end on paper or a whiteboard: requirements, capacity estimation, high-level diagram, bottlenecks, and deep dives into two or three components. Compare your design against reference solutions and note the gaps. Self-practice builds knowledge, but delivery is a separate skill, so do at least two or three live mock interview rounds for system design with a senior engineer before your actual interviews.

Use a fixed five-step framework: clarify functional and non-functional requirements, estimate scale in terms of users, QPS, and storage, draw a high-level design, deep-dive into the components the interviewer probes, and finish with bottlenecks and trade-offs. Spend the first 5–10 minutes asking questions instead of jumping straight to the diagram, since starting to draw immediately is the most common reason candidates fail this round. Thinking aloud and checking in with the interviewer matters as much as the final architecture.

Grokking the System Design Interview is a popular text-based course that teaches recurring design patterns through frequently asked problems like URL shorteners, chat systems, and news feeds. It is a good starting point because it builds vocabulary and gives you templates for common questions. That said, finishing the course alone rarely clears interviews, because the interview tests your live reasoning, not recall. Pair it with your own timed practice and feedback through mock rounds or a mentor.

The System Design Interview book by Alex Xu (Volume 1 and Volume 2) is the most widely recommended starting point for good reason: Volume 1 covers core concepts like load balancing, caching, and consistent hashing with step-by-step designs, while Volume 2 goes into more advanced systems. It is excellent for building fundamentals, but pair it with hands-on practice and discussion, since books teach you solutions while interviews test how you think under pressure. Complete beginners should first get comfortable with databases, networking, and basic backend concepts.

In India it typically runs: resume shortlisting, an online coding assessment, one or two DSA-focused technical rounds, a system design or low-level design round for experienced roles (techno-managerial rounds at senior levels), a hiring manager or behavioral round, and finally an HR discussion covering notice period and compensation. Service-based companies often add aptitude tests and group discussions for freshers. Knowing the exact round structure of your target company lets you prepare each stage deliberately instead of randomly.

Freshers are mostly tested on DSA (arrays, strings, linked lists, trees, and basic dynamic programming), OOPs concepts, DBMS and SQL queries, operating systems (processes, threads, deadlocks), and computer networks basics, followed by deep questions on the projects listed on your resume and a short HR round. Be ready to explain every design decision in your projects, because interviewers use them to verify whether your skills are genuine. Clear communication while solving often separates selected candidates from rejected ones.

Give yourself 8–12 weeks: solve 150–200 quality DSA problems instead of hundreds of random ones, revise CS fundamentals like OS, DBMS, and OOPs, keep 2–3 resume projects you can defend in depth, and add basic system design if you have over a year of experience. Include weekly mock interviews covering DSA, system design, and techno-managerial rounds, since most candidates lose offers on delivery rather than knowledge. Finally, prepare STAR-format behavioral stories and tailor your resume to each job description.

Google's process usually involves a phone screen followed by onsite rounds covering data structures and algorithms, coding, system design for more senior levels, and a Googleyness/behavioral assessment. Realistically you need 3–6 months of focused preparation: strong command over DSA at medium-hard difficulty, clean and communicable code, design practice matched to your seniority, and rehearsed behavioral examples. Timed mock interviews with a senior engineer acting as interviewer make a far bigger difference than passively solving more problems.

A resume review is a detailed critique of your resume by someone experienced in hiring, checking structure, impact-driven bullets with metrics, ATS-friendly keywords, relevance to the roles you are targeting, and red flags like vague responsibilities. In India, a CV review means the same thing, as the terms are used interchangeably. Since recruiters spend under a minute on the first scan, a review by an actual software engineer or hiring manager catches problems that friends and online checklists usually miss.

Paste your resume along with the target job description and use a detailed resume review prompt, asking it to check ATS keyword gaps, weak duty-based bullets, missing metrics, formatting issues, and relevance to the role. This works well as a first pass, but AI cannot judge how a hiring manager in your domain actually reads resumes, and it often adds generic filler. Treat ChatGPT as step one, then get a human review from an experienced engineer or mentor before applying. Many mentors, such as Gaurav Raj, offer resume review over a priority DM or a call.

Realistic free options include seniors and connections on LinkedIn, peer review groups, online communities where volunteers critique resumes, and free AI tools for a basic scan. The trade-off is that free feedback tends to be generic or inconsistent, which is useful for formatting and obvious errors but unreliable for positioning yourself for a specific role or salary jump. If you are applying seriously, one paid review by a domain expert usually costs less than the interviews a strong resume helps you land.

Check whether the reviewer has actually worked or hired in your domain, since an engineer understands technical resumes far better than a generalist writer; whether feedback is line-by-line and specific rather than generic tips; and whether they align your resume to a target job description instead of only fixing grammar. Also look for someone who explains the reasoning so you can update the resume yourself later. Be cautious of services promising guaranteed interviews — what you want is honest, detailed critique you can act on.