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Backend & Platform

Published: January 20, 2026 | Updated: January 20, 2026

What is Backend & Platform?

Backend & Platform is the engineering work that powers apps behind the scenes: APIs, databases, infrastructure, security, and reliability. If the product is a house, backend builds the plumbing and electricity so everything runs safely and fast.

Typical problems solved
  • Designing and building APIs that mobile/web apps call
  • Modeling data and choosing databases (SQL/NoSQL)
  • Ensuring speed and scalability under high load
  • Authentication, authorization, and security controls
  • Background jobs, queues, and event-driven processing
  • Deployments, observability, and cost control
How it looks in the real world
  • Adding a new endpoint for the mobile app release
  • Refactoring a slow database query and adding an index
  • Containerizing services and rolling out with CI/CD
  • Investigating a production incident with logs and metrics
  • Reducing cloud costs by optimizing storage and caching

Who this is for

  • You enjoy systems thinking: how parts connect and scale
  • You like debugging, testing ideas, and improving reliability
  • You prefer building foundations over pixel-perfect visuals
  • You are comfortable learning tools and reading docs

Prerequisites

  • Comfortable with at least one programming language (e.g., Python, Java, Go, JavaScript/TypeScript, or C#)
  • Basic terminal, Git, and problem-solving skills
  • High-level understanding of HTTP and the web
Nice-to-have
  • SQL basics (SELECT, JOIN, WHERE, indexes)
  • Familiarity with containers (Docker) and Linux

Careers inside this direction

Common roles you can grow into:

  • Backend Engineer — Designs, builds, and operates server-side applications and APIs. Works with databases, caching, security, and performance.

Explore the role card below for responsibilities, skills, and starter projects.

Where you can work

  • Industries: fintech, e-commerce, healthtech, gaming, media, logistics, SaaS, cybersecurity, AI/ML platforms
  • Company types: startups, scale-ups, big tech, consultancies, product companies, cloud providers, NGOs, gov tech
  • Team setups: product squads, platform/infra teams, SRE/DevOps, data platform teams

Salary ranges by stage

Approximate global ranges in USD. Varies by country/company; treat as rough ranges.

  • Junior: $50k–$90k
  • Mid-level: $90k–$140k
  • Senior/Staff: $130k–$200k+

Growth map

Foundations → Junior
  • Build CRUD APIs; understand HTTP, REST; basic auth
  • Solid in one language + framework
  • SQL modeling, transactions, indexes
  • Write tests; use Git effectively
Junior → Mid
  • Design modular services; async jobs and queues
  • Observability: logs, metrics, tracing, alerting
  • Performance troubleshooting and caching
  • Secure coding: input validation, secrets, least privilege
  • CI/CD, containerization, cloud basics
Mid → Senior
  • System design for scale, resiliency, and cost
  • Data migrations with zero/low downtime
  • Mentoring, code reviews, technical leadership
  • Incident response and postmortems
  • Architecture choices: monolith vs microservices, event-driven patterns

Tools & stack overview

Languages & frameworks
  • Python (FastAPI, Django), Java (Spring), Go (Gin/Fiber), Node.js/TypeScript (Express/Nest), C# (.NET)
Datastores
  • Relational: PostgreSQL, MySQL
  • NoSQL: MongoDB, DynamoDB
  • Caches: Redis, Memcached
  • Search/analytics: Elasticsearch, OpenSearch
Messaging & streaming
  • RabbitMQ, Kafka, SQS/SNS, Google Pub/Sub
DevOps & platform
  • Containers: Docker
  • Orchestration: Kubernetes (basics)
  • CI/CD: GitHub Actions, GitLab CI
  • Cloud: AWS, GCP, Azure
Observability & quality
  • Monitoring: Prometheus, Grafana
  • Logging: ELK/EFK stacks
  • Tracing: OpenTelemetry, Jaeger
  • Testing: unit, integration, contract tests

Beginner roadmap (6 weeks)

A focused plan you can complete in 4–8 weeks. Pace it as needed.

  1. Week 1: Core programming refresh
    • Variables, types, control flow, functions
    • Data structures: arrays/lists, maps/dicts, sets
    • Error handling and basic testing
    • Daily mini-task: implement a simple calculator with tests
  2. Week 2: HTTP + API basics
    • Build a CRUD REST API with one resource (e.g., /tasks)
    • Add validation and simple auth (API key or basic JWT)
    • Document endpoints with OpenAPI/Swagger
    • Mini-task: return proper status codes for common errors
  3. Week 3: Databases + SQL
    • Model entities and relationships
    • Implement queries, indexes, and migrations
    • Transaction basics and avoiding N+1 problems
    • Mini-task: write a JOIN query and add an index to speed it up
  4. Week 4: Async work + caching
    • Add a background job (email or report generator)
    • Introduce a queue (in-memory or lightweight broker)
    • Add Redis caching for a hot endpoint
    • Mini-task: measure before/after latency
  5. Week 5: Testing, logging, and errors
    • Unit tests for handlers/services
    • Integration test with a real or test database
    • Structured logs and correlation IDs
    • Mini-task: create a graceful error handler
  6. Week 6: Packaging & deploy
    • Containerize with Docker
    • Add a basic CI pipeline (build, test)
    • Deploy to a low-cost environment (local VM or free-tier cloud)
    • Mini-task: create a health endpoint and readiness checks
Stretch goals
  • Add role-based access control and rate limiting
  • Introduce OpenAPI client generation for a mock frontend
  • Add metrics (request duration, DB time) with Prometheus format

Common mistakes

  • Skipping tests — increases risk when refactoring
  • Overengineering microservices — start with a well-structured monolith
  • Ignoring observability — logs/metrics/traces save hours during incidents
  • Weak data modeling — leads to slow queries and complex code
  • Hardcoding secrets — always use environment variables or a secrets store

Mini project ideas (build to learn)

Task Tracker API

Build a multi-user task API with CRUD, due dates, and labels.

  • Users + auth (JWT)
  • Tasks with indexing on status+due_date
  • Search by text and label
  • Rate limiting per user
  • Dockerized app + database
Analytics Event Collector

Accept client events, queue them, and batch-insert into a warehouse table.

  • POST /events endpoint with validation
  • Queue or background worker
  • Batch writes and retry with exponential backoff
  • Dashboard metrics: events/min, failures
Image Processing Service

Upload, resize, and serve images with caching.

  • Upload endpoint with size/type checks
  • Background resize job
  • CDN-like caching headers
  • Signed URLs for access

Learning path

  • Pick a language track (Python, Java, Go, Node/TS, or C#) and one web framework
  • Learn RESTful API design and security basics
  • Get comfortable with SQL and a relational database
  • Add async processing and caching
  • Introduce testing, logging, and metrics
  • Containerize and set up CI; deploy to a simple environment
  • Practice system design with small, realistic diagrams and trade-offs

Next steps

  • Take the quick fit test on this page to gauge your alignment. Everyone can try it; logging in will save your progress.
  • Review the Careers inside this direction section and pick Backend Engineer to start.
  • Choose a language track and begin the 6-week roadmap. Build one mini project per week.

Aptitude Test

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