Interview Preparation Roadmap | Bohdan Koval

Target role

Choose a Senior+ role to reveal area ROI and the topics worth prioritizing. Your choice is remembered across every roadmap.

How this collection fits together

Coding practice tracks are where you grind problems — DSA is the anchor; Concurrency and Databases are independent spin-offs with their own progress.
DSA supplements are quick references tied to the main DSA roadmap — use them for review, not as a substitute for doing the problems.
System Design Use Cases is a curated index of external case studies (Hello Interview, ByteByteGo, Grokking, etc.) — links only, no in-repo theory.
Deep-dive references cover in-repo theory senior loops probe — networking through AI systems — without LeetCode-style autograding. Pair them with System Design Use Cases for external timed case walkthroughs.

Learning Path → topology mapSee the full curriculum on one horizontal progression map — grouped stages, parallel tracks, prerequisites, and rolled-up progress. Click a stage for detail.

System Design Use Cases

External case-study references only — curated links to Hello Interview, ByteByteGo, Grokking (DesignGurus.io), and other Senior/Staff-depth writeups. No in-repo theory; complements the deep-dive tracks below.

System Design Case Studies (external)≈83hSpecific chapters and problem breakdowns — URL shortener, news feed, Uber, payments, and 40+ more. Time-boxed further reading, paid and free.

Coding practice

Problem-solving roadmaps with theory, curated resources, and hand-picked practice problems — each with its own progress tracking.

DSA Interview Roadmap≈235hThe core algorithms and data structures path — arrays through graphs and DP, with LeetCode practice, interview countdown, and daily targets.

Concurrency & Multithreading Roadmap≈29hMutexes, semaphores, deadlocks, thread pools, and classic coordination problems — language-agnostic theory with reference implementations.

Practical Coding Rounds≈11hBug-squash, repository-extension, refactoring/code-review, TDD, API integration, machine coding, and AI-allowed live coding — the non-LeetCode formats startups and scaleups now run, in Python, Java, and JavaScript.

SQL Interview Roadmap≈15hSQL query-writing for coding interviews — filtering, joins, aggregation, subqueries, CTEs, and window functions.

DSA supplements

Quick-reference material that supports the main DSA track — use alongside or after your first pass through the roadmap.

Full Reference SheetSignal, approach, pitfall, and complexity per subtopic, plus a tiny code template — a fast review pass once you've done the work.

Programming Language ManualPython, Java, Go, and JavaScript side by side — memory layout, comparators, overflow, GC and boxing quirks behind every pattern.

Deep-dive references

Theory-heavy guides for senior+ loops — brief overviews and curated readings with time estimates, not LeetCode-style practice tracks.

Networking for Interviews≈14hTCP/UDP, DNS, TLS, HTTP/1.1–3, load balancing, and CDN caching — sized for senior FAANG verbal depth, not a networking degree.

Communication & Data Transfer≈36hHow services talk — REST, JSON:API, GraphQL, gRPC, tRPC, WebSockets, WebRTC, webhooks, and terabyte-scale bulk transfer. Builds on Networking.

Microservices Patterns≈29hService discovery, API gateways, BFF, service mesh, event sourcing, CQRS, and platform resilience — assembling many services at FAANG scale.

Security for Engineers≈23hApplication security for senior SWE loops — OAuth/JWT, OWASP, XSS/CSRF/CORS, API hardening, secrets, PII, and secure SDLC. Not a security-engineer cert track.

Operating Systems Reference≈26hCPU and memory virtualization, scheduling, paging, file systems, I/O, and containers — grounded in OSTEP.

OOD & Low-Level Design Reference≈45hSOLID, design patterns, LLD interview process, and classic problems — parking lot, elevator, chess, LRU cache, rate limiters, connection pool.

Distributed Systems for Interviews≈43hCAP, consistency, replication, partitioning, Raft, sagas, and Kafka semantics — multi-node correctness for senior loops. Topic 10 adds optional in-memory coding exercises.

Databases Reference≈39hHow data is stored — RDBMS internals, schema design, sharding, NoSQL, object storage, data lakes, and columnar/search engines.

Data Engineering Reference≈49hPipelines at FAANG scale — Spark, Flink, Airflow, lakehouse ELT, dbt, data quality, and production ops. Optional Deep Cuts for Kafka, CDC, and Beam.

Observability Reference≈30hLogs, metrics, OpenTelemetry tracing, SLOs and burn-rate alerting, Datadog, Grafana LGTM, Splunk, and production debugging.

AI Engineering Reference≈34hProfessional LLM use for senior engineers — fundamentals, prompting, Cursor workflows, RAG, MCP, agents, model selection, and team governance.

AI Systems Reference≈44hProduction AI at scale — serving, RAG pipelines, guardrails, evals, cost, rollouts, and enterprise compliance. Optional Deep Cuts for inference infra (vLLM, GPU fleets).