Database Engineering & Data Systems Topics
Database design patterns, optimization, scaling strategies, storage technologies, data warehousing, and operational database management. Covers database selection criteria, query optimization, replication strategies, distributed databases, backup and recovery, and performance tuning at database layer. Distinct from Systems Architecture (which addresses service-level distribution) and Data Science (which addresses analytical approaches).
Database Forensics and Data Recovery
Investigative and recovery work on databases: examining database and application artifacts, transaction logs, and residual data to reconstruct activity, plus recovering corrupted or deleted data. Covers evidence integrity and forensic method applied to database systems. A specialized surface for security and forensics roles.
Backup and Disaster Recovery
Keeping data durable and recoverable when systems fail: backup design (full, incremental, differential, and snapshot strategies; point-in-time recovery), backup verification and restore testing, retention and archival policy (including compliance retention and legal holds), encryption and key management for backups, and disaster-recovery planning measured against recovery-time and recovery-point objectives (RTO/RPO). Tests whether a candidate can design a backup strategy that actually restores, choose the right retention tier for a business's downtime and data-loss tolerance, and operate backup systems safely under failure, compliance, and ransomware threats. Distinct from code-level fault-tolerance patterns (circuit breakers, retries, bulkheads) and multi-region failover architecture, which belong to high-availability-and-disaster-recovery.