Back-End Developer interview questions

The best practices for database schema design in large-scale applications include normalization up to a suitable normal form to reduce redundancy, effective indexing for query optimization, partitioning and sharding strategies for horizontal scalability, use of foreign keys and constraints to maintain data integrity, and establishing clear documentation and naming conventions for tables and fields.

Strategies for designing RESTful APIs that handle heavy data traffic include implementing pagination and filtering to limit payload size, caching frequent responses, applying rate limiting and throttling, optimizing payload serialization, leveraging HTTP compression, using asynchronous processing for resource-intensive tasks, and monitoring for bottlenecks.

Data consistency and integrity in distributed database systems can be ensured by leveraging distributed transactions, applying ACID or BASE principles as needed, using consensus algorithms such as Paxos or Raft, employing data replication strategies, and continuously monitoring and reconciling data discrepancies across nodes.

Techniques for optimizing SQL queries in high-concurrency environments include indexing hot columns, minimizing the use of subqueries and joins, avoiding SELECT *, leveraging query caching, using parameterized queries to prevent recompilation, analyzing query plans, and periodically archiving old or infrequently accessed data.

Asynchronous programming workflows can be structured using message queues, event loops, non-blocking I/O operations, promises or async/await patterns, background job processing frameworks, and distributed task queues to decouple long-running or resource-intensive tasks from user-facing endpoints.

Transactional workflows across multiple microservices are handled using approaches such as the Saga pattern, two-phase commit (2PC), event sourcing combined with eventual consistency, idempotent operations, and compensating transactions to maintain data consistency even in the event of failures.

Robust API versioning involves using URI versioning, custom headers, or content negotiation, maintaining backward compatibility, providing comprehensive documentation for each version, deprecating obsolete versions with clear communication, and ensuring automated testing for all supported versions.

API performance can be monitored, logged, and analyzed using Application Performance Monitoring (APM) tools, structured logging, trace IDs for end-to-end request tracking, metrics collection (such as latency, error rate, and throughput), and regular review of logs to detect bottlenecks and prioritize optimization efforts.

Advanced patterns for asynchronous error handling and retry mechanisms include exponential backoff, circuit breaker, dead-letter queues, bulkheading, fallback procedures, and idempotent operation design to ensure reliable processing and system stability.

Database security in production is enforced by implementing role-based access control, encrypting data at rest and in transit, auditing and logging all access and queries, enforcing strong authentication, regular patching, periodic security assessments, and following the principle of least privilege.