How to Interview at Big Tech (FAANG and Beyond)

What "Big Tech" Interviews Are Actually Measuring

Big tech FAANG interview tips usually focus on coding and system design. That's only half the picture. The interview loop at companies like Google, Meta, Amazon, Apple, and Microsoft is designed to evaluate across multiple dimensions — and you can fail on behavioural rounds even with perfect technical scores.

The dimensions assessed across a typical 5–6 round loop:

1. Coding (2–3 rounds) — algorithm fluency, code quality, problem decomposition
2. System design (1–2 rounds) — scalability, tradeoffs, architecture
3. Behavioural / leadership principles (1–2 rounds) — how you've operated, how you handle adversity, how you collaborate
4. Hiring committee calibration — all scorecards are reviewed holistically; you're not just summing rounds

The bar is calibrated to the level you're interviewing for, not in absolute terms. A senior engineer who passes the junior bar won't get an offer.

Understanding the Levelling System

Every big tech company has a levelling framework. The same job title at different levels requires fundamentally different interview performance.

If you're interviewing for L5 and solving at L4 speed, you won't get the offer — even if you get the answer right. Big tech interviewers are explicitly asked to calibrate against a level bar.

The Coding Interview: Beyond LeetCode

Everyone knows you need to practice algorithms. The part most candidates miss:

Speed matters less than clarity. Interviewers at Google and Meta are not racing to see if you can solve hard in 15 minutes. They're watching whether you communicate your thinking, ask clarifying questions, and write clean code under pressure.

A strong coding interview looks like this:

1. Clarify before coding — "Before I start, let me make sure I understand the constraints. Is input sorted? Can I assume ASCII-only strings?"
2. Talk through your approach — "My first instinct is a brute force O(n²). I can see a way to get this to O(n log n) with a sorted set. Shall I go with that?"
3. Write clean, readable code — meaningful variable names, comments on tricky logic
4. Test with edge cases — empty input, single element, negative numbers, overflow
5. Discuss complexity — always offer time and space complexity unprompted

The candidates who fail often have the right solution but work silently, then present code without explanation. Interviewers can't give credit for reasoning they can't see.

System Design: How to Approach It

System design rounds are the highest-variance part of the loop. There's no single right answer — the interviewer is evaluating your judgment.

Framework for any system design question:

1. Clarify requirements (5 minutes) — functional requirements, non-functional (scale, latency, availability), constraints
2. Estimate scale — "At 10M daily users, with 100 actions per user per day, that's ~11,500 requests per second. We're in the high-throughput territory."
3. High-level design — client, API layer, services, databases, caching
4. Deep dive one component — the interviewer will usually direct this
5. Address tradeoffs — consistency vs. availability, latency vs. cost, simplicity vs. scalability

Where candidates lose points: jumping to a distributed microservices design before establishing that it's needed, or spending all their time on the happy path without discussing failure modes.

Behavioural Rounds: Leadership Principles Are Scored

At Amazon, leadership principles aren't just talking points — they're a scoring rubric. At Google, the "Googleyness" round uses behavioural questions to assess culture fit and how you handle conflict, failure, and ambiguity.

Prepare stories across these themes:

• A project that failed or shipped late — what was your role?
• A time you disagreed with your manager or a stakeholder — how did you handle it?
• Your highest-impact contribution and how you measured it
• A time you had to prioritise ruthlessly — what didn't you do?
• A time you influenced without authority

Use STAR format. At big tech, "result" should include measurable impact wherever possible. "The feature launched on time" is not a strong result. "The feature launched on time, drove a 14% increase in DAU over 30 days, and became a template for subsequent launches" is.

How to Prepare: A 6-Week Timeline

Weeks 1–2: Coding foundations

• Focus on patterns: two pointers, sliding window, BFS/DFS, dynamic programming, binary search
• 1–2 problems per day on LeetCode, medium difficulty
• Review solutions after each problem — don't just celebrate getting it right

Weeks 3–4: System design

• Read Designing Data-Intensive Applications (at least chapters 1–6)
• Practice: URL shortener, Twitter feed, distributed cache, rate limiter
• Practice narrating your design out loud

Weeks 5–6: Behavioural + mock loops

• Write and rehearse 10–12 STAR stories covering all key themes
• Do at least 2–3 full mock loops (coding + design + behavioural) with a partner or coach
• Research the specific company's engineering blog, values, and recent launches

The Debrief and Offer Process

After the loop closes, your scorecards go to a hiring committee. You are not evaluated individually by round — the committee looks for signal across all rounds.

Things that can save a borderline candidate:

• One extremely strong round (often system design or behavioural at senior levels)
• Consistent "strong hire" signals rather than mixed scores

Things that fail candidates regardless:

• A "no hire" from two or more interviewers
• A failed coding round at levels where it's mandatory
• Significant behavioural red flags (e.g., inability to describe taking ownership)

If you receive a "no offer" decision, most big tech companies will tell you the category that was weakest. Use that feedback for your next attempt.

Practice This Now

There's a measurable difference between knowing system design frameworks and being able to drive a 45-minute design discussion fluently. Practice is not optional.

Try a free session on Interview Sparring →