Why FAANG Still Cares About DSA in 2025

Why FAANG Still Cares About DSA in 2025 Thumbnail

If you’re preparing for FAANG interviews in 2025 (like me right now 👀), you’ve probably asked yourself:
“Why the heck are they still asking me about reversing a linked list when nobody in real life codes that from scratch?”

Fair question. But the answer is deeper than just “because tradition.” Let’s break it down.


🚀 1. DSA shows how you think under pressure

At FAANG-level interviews, you’re not being hired to write just code. You’re being hired to:

  • Break down a vague problem
  • Find multiple ways to solve it
  • Pick the best one under constraints

DSA problems are the fastest way to test this.
For example:

  • Two Sum problem – Do you brute force, or do you immediately see the hashmap optimization?
  • Graph traversal – Do you BFS or DFS? Can you explain why?

It’s less about solving Two Sum itself, more about showing that your brain defaults to “optimize and scale.”


🏗️ 2. Real-world systems secretly run on DSA

Most devs don’t directly implement heaps, tries, or segment trees at work.
But… the systems you’re building on top of do.

Examples:

  • Google Search → Tries, inverted indexes, heaps.
  • Netflix Recommendations → Graph algorithms, dynamic programming tricks.
  • Databases (MySQL, MongoDB) → B-Trees, Hash Indexes.
  • Load balancers → Queues, hashing, priority scheduling.

If you understand the DSA under the hood, you’ll design better systems because you know the trade-offs.


⏱️ 3. Interview Time is Limited

A full system design interview needs 45–60 minutes.
So how do they test raw problem-solving in a short span?
→ Throw you a DSA problem.

In 20–30 minutes, they can see:

  • Can you handle edge cases?
  • Do you write clean code under pressure?
  • Do you think about time and space complexity?

It’s basically the unit test for your brain.


💡 4. Senior Engineers Still Use DSA Thinking

At SDE-3+ level, you’re not coding linked lists every day.
But you are doing:

  • “How do we reduce query time from O(n) to O(log n)?”
  • “Should we shard this DB by hash or range?”
  • “Can we cache results in a trie-like structure for autocomplete?”

That’s just DSA thinking applied to real-world scale.


🏆 5. FAANG Needs a Consistent Global Filter

Imagine trying to interview thousands of candidates across the world.
DSA provides a universal, fair filter:

  • Doesn’t matter which framework you’ve used.
  • Doesn’t matter if you were a freelancer, startup dev, or from a Tier-3 college.
  • Everyone can be judged on the same foundation: problem-solving.

🔑 Takeaway

In 2025, yes — we have AI copilots, LLMs, auto-complete everything.
But DSA is still the quickest way for FAANG to test your brain’s OS.

If you’re prepping (like me), don’t just grind LeetCode blindly.
👉 Learn why an approach works, and how it connects to real-world systems.
That’s the difference between a LeetCode grinder and an engineer FAANG wants to pay 50LPA+ for.


✍️ Personal Note

I’m currently preparing for 50LPA+ SDE roles myself, and this blog is where I’ll share everything I learn along the way — from DSA to System Design to backend engineering. Writing about it helps me understand things deeper, and hopefully, it helps you too if you’re on the same journey.

Stay tuned — more blogs coming soon 🚀

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