Nehasrinivas

DSA + Data Engineer. I’ll be sharing my journey here!

[Reso @Resorcinolworks]

the checklist of companies i had while applying-

Meta
Microsoft
Google
LinkedIn
Adobe
Oracle
Atlassian
Confluent
Uber
Airbnb
Expedia
Agoda
Grab
Walmart
Wayfair
PayPal
Coinbase
Twilio
ServiceNow
Nutanix
Rubrik
UiPath
Postman
Harness
Glean
Rippling
Moveworks
HubSpot
Freshworks
Tekion
Zeta
PhonePe
Razorpay
Cashfree
Juzpay
Cred
Groww
Angel One
Kotak
Slice
Acko
CoinDCX
ShareChat
Swiggy
Meesho
Hotstar
Games24x7
Headout
Blink Health
SenseHQ
Eightfold AI
Spotnana
Tide
Tesco
GEP
Eternal (Formerly Zomato)

[Avinash Singh @AvinashSingh_20]

I might delete this -> Free AI/ML/DS Google drive resources - https://t.co/gGK7ROWjgB

[sankit @sankitdev]

Backend isn’t just APIs and CRUD.

This is the roadmap companies like Google, Meta, Amazon expect you to know.

DSA
> Companies like Google don’t care about your projects if you fail here.
> This is the real filter.
> Conquer this, and every door in tech opens.
> Struggle here, and those doors stay shut.

0. Ground Setup

Before going crazy with topics, you need:

> One main backend language (JavaScript/TypeScript, Go, Java, Rust — pick one and master it)
> Git + GitHub: branching, PRs, rebases, conflict resolution
> Linux basics: ls, cd, cat, grep, find, permissions, SSH
> Editor mastery: VS Code or any solid setup

First principles here:
> What is a program? How does source code become a running process?
> What is an OS process vs thread?
> What does it mean to run a server on a port?

You should be able to:
> SSH into a Linux box, pull a repo, install deps, run a server on a port, view it via browser

---

1. Core Backend Fundamentals

1.1 Networking and HTTP

You cannot be a strong backend engineer if HTTP is just “that thing Express uses”.

Understand:
> DNS → IP → TCP → HTTP
> Difference between IP / TCP / UDP / HTTP / HTTPS
> HTTP methods, status codes, headers, idempotency, safe methods
> REST vs RPC vs GraphQL

Practice:
> Build a backend without any framework using native http
> Parse JSON body manually
> Implement basic rate limiting
> Add API versioning (/v1, /v2)

---

1.2 API Design and Backend Architecture Basics

First principles:
> Resource modeling
> Stateless vs stateful
> Consistent naming, validation, clear errors
> Pagination, filtering, sorting

Layered architecture:
> Controller → Service → Repository (DAO)

You should be able to:
> Design APIs for Task Manager or Expense Tracker
> Keep error and response structure consistent everywhere

---

2. Databases and Data Modeling

Big companies will grill you here.

2.1 Relational Databases

SQL is non-negotiable.

Understand:
> Table, row, column, primary key, foreign key
> Normalization: 1NF, 2NF, 3NF basics
> Joins: inner, left, right, full
> Transactions and ACID
> Indexes and their impact

You should be able to:
> Instagram schema: users, posts, likes, comments, followers
> Query top posts, mutual followers
> Use migrations, not manual DB edits

---

2.2 NoSQL and When to Use It

Understand:
> Document DB vs relational DB
> Denormalization
> Event logs and analytics needs
> CAP theorem basics
> Collections, documents, indexes, aggregation pipeline

Be able to decide:
> When a feature needs SQL vs NoSQL

---

3. Authentication, Authorization and Security

3.1 Auth Basics

Understand:
> Authentication vs authorization
> State vs stateless auth
> Password hashing (bcrypt/argon2)
> Cookies: HttpOnly, Secure, SameSite
> Access vs refresh tokens
> Token revocation and rotation
> Basics of OAuth2 / OpenID Connect

You should be able to:
> Implement email/password auth with verification and forgot password
> Explain cookies vs localStorage
> Explain token invalidation strategies

---

3.2 Web Security Core

Understand:
> SQL injection, XSS, CSRF, IDOR (OWASP Top 10)
> Input validation and output encoding
> CORS and preflight

You should be able to:
> Identify common vulnerabilities in APIs
> Configure CORS correctly

---

4. Concurrency, Performance and Scalability

4.1 Concurrency and Asynchrony

Understand:
> Event loop, callback queue, microtasks
> Blocking vs non-blocking I/O
> CPU-heavy work blocks Node

You should be able to:
> Explain when to use worker threads and offloading

---

4.2 Caching

Concepts:
> In-memory vs Redis caches
> TTL, LRU, invalidation
> HTTP caching: ETag, Last-Modified, Cache-Control

You should be able to:
> Use Redis to cache DB queries and rate limit
> Plan cache keys well

---

4.3 Scaling and Architecture Patterns

Understand:
> Vertical vs horizontal scaling
> Stateless services for scale-out
> Load balancers
> Monolith vs microservices
> Sync vs async flows (queues)

Patterns:
> Circuit breaker
> Retry with backoff
> Idempotency keys for POST

You should be able to:
> Split a monolith into services and make them communicate

---

5. Messaging, Queues and Async Systems

Understand:
> RabbitMQ, Kafka, Redis streams
> Producers, consumers, delivery semantics

Use cases:
> Emails, uploads, payment pipelines, logs

You should be able to:
> Offload heavy jobs to background workers
> Build async workflows

6. Testing and Quality

Understand:
> Unit, integration, E2E tests
> Test pyramid
> Deterministic vs flaky tests

You should be able to:
> Test auth flows and business logic
> Run tests in CI (GitHub Actions or similar)

7. DevOps Basics for Backend Engineers

7.1 Containers and Deployment

Understand:
> Dockerfile basics (FROM, COPY, RUN…)
> Docker Compose for app + DB
> Environment variables and config

You should be able to:
> Containerize backend and DB
> Deploy to any cloud provider

7.2 CI/CD and Observability

Understand:
> CI pipelines: tests, lint, build
> Auto deploy workflows
> Logging and metrics

You should be able to:
> Add logging middleware with request IDs
> Monitor latency, error rate, throughput

8. System Design

This becomes crucial for big tech interviews.

Understand:
> Load balancer, app server, DB, cache, queue, file storage
> Consistency models
> API Gateway and BFF patterns
> Unique ID generation (UUID, Snowflake)

Practice on paper:
> URL shortener
> Instagram feed
> E-commerce checkout
> Notification systems

Consider:
> DB schema, caching, queue usage, failure handling

9. Domain-Specific Knowledge

Depending on role and product:

> Fintech: strong consistency, audit logs, idempotency
> E-commerce: carts, pricing, orders, inventory
> Real-time: WebSockets, SSE, backpressure

Choose what aligns with your career direction and keep grinding.

[Nehasrinivas @Nehasrinivas07]

Any data engineers here?
Let’s #connect and share insights, projects, and opportunities in the data world!

#DataEngineering #DataCommunity #Networking

[Nehasrinivas @Nehasrinivas07]

@bansalgagan2004 Hey, lets connect

[Nehasrinivas @Nehasrinivas07]

#JusticeForDoctor #JusticeForAbhaya

[Nehasrinivas @Nehasrinivas07]

@jayk_gupta Hi

[Kritika K @kritika_k__]

Tips to solve any DSA question by understanding patterns

If the input array is sorted then
- Binary search
- Two pointers

If asked for all permutations/subsets then
- Backtracking

If given a tree then
- DFS
- BFS

If given a graph then
- DFS
- BFS

If given a linked list then
- Two pointers

If recursion is banned then
- Stack

If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer

If asked for maximum/minimum subarray/ subset/options then
- Dynamic programming

If asked for top/least K items then
- Heap
- QuickSelect

If asked for common strings then
- Map
- Trie

Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space

(Source: whatsapp)

[Nehasrinivas @Nehasrinivas07]

@Nikhil_yadav20 Done

[Nehasrinivas @Nehasrinivas07]

@lalitwagh6543 Done

[Nehasrinivas @Nehasrinivas07]

Hi there, I'm looking to #Connect with people who are interested in:
DSA
Machine learning
And who can code early mornings