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 Engine Expertise
Deep practical knowledge of specific database engines, including engine internals, storage engines, concurrency and locking models, replication and failover mechanisms, backup and restore approaches, configuration defaults and version upgrade practices. Candidates should demonstrate familiarity with engine specific performance tuning patterns, tooling and extensions, common failure modes and diagnostics, and migration and compatibility considerations when moving between engines or versions. Examples include understanding PostgreSQL internals and extensions, MySQL storage engines and configuration, and how engine design affects operational choices.
Data Types and Constraints
Covers selection and implications of database data types and the use of constraints to enforce data integrity and performance considerations. Topics include numeric types and precision, integer and floating types, boolean, date and time types, fixed length and variable length string types such as CHAR and VARCHAR, long text and binary types, and semi structured types such as JSON and XML. Also includes constraint types and usage such as NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, default values, referential integrity and cascade actions. Candidates should understand storage implications, indexing trade offs, collation and encoding considerations, normalization and denormalization effects, and how type and constraint choices affect query performance, storage, and data quality.
Concurrency and Locking Management
Comprehensive understanding of how databases manage concurrent access and synchronization across transactions. Topics include transaction isolation levels and their trade offs, row level versus table level locking, lock escalation, lock timeouts, and lock contention and their effects on throughput and availability. Covers deadlock causes, detection and analysis techniques, prevention strategies and recovery patterns such as careful transaction ordering, reducing transaction duration, optimistic concurrency control, multiversion concurrency control, and retry with backoff. Includes diagnostics and monitoring approaches such as lock tables, deadlock graphs and transaction logs, as well as design practices like index design, short transactions, batching and advisory locks to reduce contention.
Modern Database Technologies
Evaluate familiarity with contemporary database technologies and the trade offs for different use cases. Areas include relational and non relational systems, distributed NewSQL alternatives, managed cloud databases and platform services, column oriented and analytical stores, data warehouse and lakehouse designs, stream processing and change data capture, replication and consensus protocols, multi region and active active patterns, serverless databases, migration strategies, and criteria for selecting technologies based on consistency requirements, latency goals, cost, and operational complexity.
Set Operations and Complex Aggregations
Understanding UNION, UNION ALL, EXCEPT, INTERSECT operations and their performance implications. Complex GROUP BY queries, HAVING clauses, and multi-level aggregations.
Troubleshooting Common Database Issues
Systematic approach to investigating common problems: slow queries, connection issues, disk space problems, long-running transactions, deadlocks, and failed jobs. Understanding how to gather diagnostic information (logs, metrics, system information) and narrow down root causes. Knowledge of basic resolution strategies for each class of issue. Understanding when to escalate vs. when to resolve independently at junior level.
Caching and Connection Management
Covers caching strategies and connection management used to improve database performance and scalability. Topics include caching patterns such as local in memory caches and distributed caches, cache eviction policies and time to live strategies, cache invalidation and coherence trade offs, read through and write through approaches, cache warming and prefetching, the impact of caching on consistency and correctness, instrumentation and monitoring of cache hit and miss rates, sharding and partitioning of caches, connection pooling design including pool sizing, connection reuse, leak detection, prepared statement caching, transaction boundary interactions with pooling, and operational concerns when using caches and pools in cloud and multi region deployments.
Database Technologies and Environments
Describe the database systems and deployment environments you have administered, including relational databases and nonrelational databases, as well as cloud managed database services and on premise deployments. Explain the depth of your experience with specific engines and versions, typical workloads and performance characteristics, operational responsibilities such as backups, patching, upgrades, replication and failover configuration, security and access control, capacity planning, and migration work. Discuss deployment models you have used such as virtual machines, containers, and managed platform services, integration with application stacks and drivers, connection pooling, and supporting tooling for monitoring, automation, and observability. Include experience choosing technologies for particular workloads, trade offs you considered, and any work with complementary services such as caching, search, or data warehousing.
Database Scalability and High Availability
Architectural approaches and operational practices for scaling and maintaining database availability. Topics include vertical versus horizontal scaling trade offs; replication topologies, leader and follower roles, read replicas and replica lag; read write splitting and connection pooling; sharding and partitioning strategies including range based, hash based, and consistent hashing approaches; handling hot partitions and data skew; federation and multi database federation patterns; cache layers and cache invalidation; rebalancing and resharding strategies; distributed concurrency control and transactional guarantees across shards; multi region deployment strategies, cross region failover and disaster recovery; monitoring, capacity planning, automation for failover and backups, and cost optimization at scale. Candidates should be able to pick scaling approaches based on read and write patterns and explain operational complexity and trade offs introduced by distributed data.