Most software engineer interview processes at top tech companies follow a similar structure: (1) a recruiter screening call (15–30 min), (2) a technical phone or video screen with 1–2 coding problems (45–60 min), and (3) an on-site or virtual final round with 4–6 interviews covering coding, system design, and behavioural questions. The whole process typically takes 2–6 weeks. Some companies like Stripe and Atlassian substitute take-home projects for live coding at the screening stage.

At most mid-to-large tech companies, expect 5–7 total interactions: 1 recruiter screen + 1–2 technical screens + 3–5 final round panels. FAANG companies (Google, Meta, Amazon, Apple, Netflix) tend to run 4–6 final-round interviews in a single loop. Startups and scale-ups typically run 3–5 interviews total. Always ask your recruiter for the exact breakdown early in the process.

Entry-level (L3/SWE-I) interviews focus on coding proficiency, understanding of core data structures and algorithms, and basic debugging skills. Senior (L5/L6) interviews add a system design round (1–2 interviews on designing scalable distributed systems), a leadership/behavioural round assessing cross-team influence, and deeper product and architectural thinking. At the senior level, interviewers assess how you make decisions, not just whether you can code. The coding problems also tend to be harder and the bar for complexity analysis is higher.

Use the language you know best — interviewers care about clear, correct, working code, not the language choice. Python is the most popular for coding interviews due to its concise syntax and built-in data structures. Java and C++ are also widely accepted. JavaScript is fine if you're interviewing at a front-end or full-stack focused company. Avoid esoteric or unfamiliar languages. If a company has a preference, your recruiter will mention it.

For a first FAANG or top-tier tech interview: plan for 8–12 weeks of focused preparation (1–2 hours per day). This is enough time to cover core algorithms and data structures, complete 100–150 LeetCode problems across easy/medium/hard, and practise 8–10 system design problems. If you have prior experience with technical interviews or a strong CS background, 4–6 weeks of targeted review may suffice. The key is consistency over intensity — spaced practice beats cramming.

No. Top tech companies including Google, Apple, and Meta have explicitly removed degree requirements. What matters is demonstrating the knowledge typically acquired through a CS degree: data structures, algorithms, system design, and software engineering fundamentals. Many successful engineers at FAANG are self-taught or bootcamp graduates. That said, you'll need to cover the same material on your own — focus on algorithms (sorting, searching, graph traversal), data structures (trees, heaps, hash maps), and object-oriented or functional design principles.

Google places heavy emphasis on algorithmic problem-solving (often harder than LeetCode Hard difficulty) and system design at Google scale (billions of users). Their interviews have a strict rubric and the bar for clarity of reasoning is very high. Meta (formerly Facebook) tends to ask more product-oriented system design questions and places strong weight on behavioural interviews aligned to their core values. Meta coding rounds are typically LeetCode Medium difficulty. Both are rigorous, but Google skews more algorithmic while Meta balances product thinking and engineering. See the Google Software Engineer and Meta Software Engineer guides for company-specific prep.

In the US, total compensation for software engineers varies significantly by company and level. Entry-level (L3 at Google / E3 at Meta): $180k–$280k total comp. Mid-level (L4/E4): $250k–$400k. Senior (L5/E5): $350k–$600k. Staff (L6/E6): $500k–$900k+. Base salaries are typically $130k–$250k with the remainder in stock (RSUs) and bonus. Outside of FAANG, total comp is typically 30–50% lower. For UK and European markets, salaries run roughly 50–60% of US equivalents in absolute terms but often with stronger benefits. Always negotiate — the first offer is rarely the final one.

Core topics: horizontal vs vertical scaling, load balancing, database sharding and replication, SQL vs NoSQL trade-offs, caching strategies (CDN, Redis, in-memory), message queues (Kafka, SQS), API design (REST, GraphQL, gRPC), CAP theorem and consistency models, and microservices vs monolith trade-offs. Practice designing real systems: URL shortener, ride-sharing app, social media feed, search autocomplete, video streaming platform. Aim to practise 1–2 system design problems per week in the run-up to interviews.