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).
Geospatial Data and Querying
Explore how to store index partition and query location based data at scale. Topics include spatial data types and spatial libraries, spatial indexing techniques and tree structures for range and nearest neighbor queries, geohash and tile based partitioning, coordinate reference systems and projection issues, and distance calculation methods. Candidates should describe query patterns for common geospatial use cases such as nearest neighbor search geofencing route matching and area aggregations, and explain trade offs between accuracy latency and storage cost as well as approaches to caching map tiles and handling moving entities.
Data Management and Storage
Knowledge of data storage and management strategies for large scale systems. Includes choosing between relational and non relational stores, understanding consistency models and transactional guarantees, replication and partitioning strategies, indexing and query patterns, caching approaches, data retention and backup policies, and the operational trade offs between latency throughput durability and cost. Candidates should explain how data choices constrain application design and influence program decisions.
Database Selection and Trade Offs
How to evaluate and choose data storage systems and architectures based on workload characteristics and business constraints. Coverage includes differences between relational and nonrelational families such as document stores, key value stores, wide column stores, graph databases, time series databases, and search engines; mapping query patterns and latency requirements to storage options; trade offs between strong consistency and eventual consistency and their impact on availability and complexity; partition key design, replication strategies, and high availability considerations; operational concerns including backups, monitoring, vendor and cost trade offs, migration or hybrid strategies, and when to adopt polyglot persistence. Senior level discussion includes selecting specific managed services and reasoning about expected load patterns, failure modes, and operational burden.
Database Design and Query Optimization
Principles of database schema design and performance optimization including relational and non relational trade offs, normalization and denormalization, indexing strategies and index types, clustered and non clustered indexes, query execution plans, common table expressions for readable complex queries, detecting missing or redundant indexes, sharding and partitioning strategies, and consistency and availability trade offs. Candidates should demonstrate knowledge of optimizing reads and writes, diagnosing slow queries, and selecting the appropriate database model for scale and consistency requirements.