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Prepare for data engineering interviews: SQL deep dives, Python coding, system design, data modeling, behavioral questions, and take-home project tips.
How real-world systems use data structures and algorithms — B-trees in databases, skip lists in Redis, inverted indexes in search, Dijkstra in routing, DAGs in Git, consistent hashing, and Bloom filters.
Master API design with REST principles, GraphQL trade-offs, gRPC for microservices, pagination strategies, rate limiting, and authentication patterns. Learn why Stripe's API is the gold standard.
Master database replication patterns — single-leader, multi-leader, and leaderless. Learn about replication lag, conflict resolution, quorum reads, and how Slack handles replication at scale.
Deep dive into ACID properties, isolation levels, and distributed transactions. Understand dirty reads, phantom reads, two-phase commit, the saga pattern, and how Stripe handles payment consistency.
Understand what makes distributed systems hard. Learn consensus algorithms (Paxos, Raft), leader election, distributed locking, vector clocks, gossip protocols, and how CockroachDB achieves distributed SQL.
How Instagram scaled Django to 2B+ users. Covers feed generation, image processing pipelines, Stories architecture, and PostgreSQL sharding strategies.
An honest look at microservices vs monoliths. Learn service communication, API gateways, database-per-service, distributed tracing, and how Amazon's migration shaped the industry.
Understand the networking stack from TCP/IP to HTTP/3. Learn DNS resolution, the TLS handshake, WebSockets vs SSE, and how CDNs reduce latency — all through practical analogies.
How Netflix evolved from DVD rental to a global streaming platform serving 250M+ subscribers. Covers microservices, Open Connect CDN, recommendations, and Chaos Engineering.
Master scalability patterns including horizontal scaling, stateless services, read replicas, CQRS, database partitioning, and async processing. See how Instagram handles 2B+ users.
How Spotify streams 100M+ songs to 600M+ users. Covers audio streaming, Discover Weekly ML, the squad/tribe model, event-driven architecture, and offline mode.
Compare relational and non-relational databases from first principles. Learn ACID properties, NoSQL types, polyglot persistence, and when to pick each — with real migration stories from Uber and Netflix.
How Twitter delivers 500M tweets/day to 300M+ timelines. Covers the fanout problem, hybrid push/pull, real-time search with EarlyBird, and the celebrity tweet challenge.
How Uber matches millions of riders with drivers in real-time. Covers geospatial indexing with H3, surge pricing, ETA prediction, and their migration from Python to Go.
How WhatsApp served 2 billion users with just 50 engineers. Covers Erlang/BEAM concurrency, end-to-end encryption, message delivery, and extreme engineering efficiency.
How YouTube serves 1B+ hours of video per day. Covers the video upload pipeline, adaptive bitrate streaming, recommendation engine, and live streaming architecture.
Understand what system design is, why it matters for engineers, the core building blocks of scalable systems, and how to approach system design interviews.
Deep dive into database indexing — B-trees, hash indexes, composite indexes, covering indexes, partial indexes, and when each strategy wins or hurts performance.
Design a distributed key-value store like DynamoDB or Redis Cluster. Covers partitioning, replication, consistency models, conflict resolution, and failure handling.
Design a proximity service like Google Maps nearby search — geohashing, quadtrees, spatial indexing, and scaling location-based queries to millions of users.
Design a distributed unique ID generator — compare UUIDs, Snowflake IDs, database tickets, and ULID for generating globally unique, sortable identifiers at scale.
Design a web crawler like Googlebot — URL frontier, politeness, deduplication, distributed architecture, and strategies for crawling billions of pages.
Compare monolithic and microservices architectures with real decision criteria, migration patterns, and code examples to help you choose the right approach for your project.
Design an API gateway that handles routing, authentication, rate limiting, and protocol translation. Covers plugin architecture, request pipelines, and scaling strategies.
Design a CDN that serves static and dynamic content from edge locations worldwide. Covers caching tiers, cache invalidation, origin shielding, and anycast routing.
Design a real-time collaborative editor like Google Docs. Covers conflict resolution with CRDTs and OT, presence awareness, cursor synchronization, and offline editing support.
Design a centralized logging system like the ELK stack. Covers log collection, structured ingestion, indexing, retention policies, and querying terabytes of logs efficiently.
Design a distributed task scheduler that handles delayed, periodic, and one-off jobs at scale. Covers sharding, time wheels, exactly-once execution, and failure recovery.
Design a scalable Domain Name System. Covers recursive and authoritative resolution, zone file management, caching, anycast deployment, and handling billions of lookups daily.
Design a checkout system that handles cart management, inventory reservation, payment orchestration, and order fulfillment. Covers saga patterns and consistency under high load.
Design a feature flag service for safe rollouts and experimentation. Covers flag evaluation, targeting rules, percentage rollouts, real-time propagation, and audit trails.
Design a time-series metrics pipeline like Prometheus or Datadog. Covers pull vs. push collection, aggregation, downsampling, storage engines, and alerting at scale.
Design an object storage system like Amazon S3. Covers metadata management, data placement, erasure coding, consistency models, and multi-tenant isolation at petabyte scale.
Design a reliable webhook delivery system. Covers event ingestion, at-least-once delivery, retry strategies with exponential backoff, payload signing, and dead letter queues.
Learn how backpressure prevents overload in distributed systems. Covers load shedding, rate limiting, buffering, and flow control patterns with examples.
Learn how Bloom filters work, why they use multiple hash functions, and where to apply them in caching, databases, and distributed systems.
Learn the circuit breaker pattern to prevent cascading failures in distributed systems. Covers states, configuration, and implementation with code examples.
Learn how connection pooling reduces overhead, compare pool sizing strategies, and configure pools for databases, HTTP, and gRPC in production systems.
Go beyond basic consistent hashing. Learn how virtual nodes solve imbalance, how rebalancing works during scale events, and real-world usage in Cassandra and DynamoDB.
Learn how CQRS separates read and write models for better scalability. Covers architecture, implementation patterns, and when CQRS is worth the complexity.
Understand event sourcing fundamentals, how it differs from CRUD, when to use it, and the real-world trade-offs you need to consider before adopting it.
Learn how to design idempotent APIs and achieve exactly-once semantics using idempotency keys, deduplication stores, and transactional outbox patterns.
Learn how the saga pattern coordinates transactions across microservices using choreography and orchestration, with compensation logic for rollbacks.
Understand how service meshes handle traffic management, observability, and security in microservices using sidecar proxies like Envoy and platforms like Istio.
A system design deep dive into building search autocomplete: trie data structures, ranking algorithms, caching strategies, data collection pipelines, and real-time update mechanisms.
A senior-engineer checklist for system design interviews: how to drive the discussion, allocate time, surface trade-offs, and avoid common traps.
A pragmatic look at the CAP theorem: what consistency and availability mean for real workloads, and how PACELC describes the trade-offs better.