Discord·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Data Engineer round at Discord, basically a coding question dressed up as a data modeling exercise. You build an in-memory game catalog and then write a few lookup functions over it. Pretty approachable if you're comfortable with dicts and basic iteration.

Questions Asked (1)

Given a list of game metadata records (name, release date, platforms, genre, publisher, optional country, Discord servers), design an in-memory data structure to store them and implement lookup functions: get a game's genre by name, get all games by genre, get the games available on the most platforms, and get all games available on exactly N platforms.

Algorithms & Data StructuresData Modeling

Author's notes

The structure part felt straightforward, just a dict keyed by lowercased name.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the data model and expected query patterns, then propose a primary storage structure (e.g., a list of game objects) plus auxiliary indexes (maps) to support fast lookups. For each required function, choose the most efficient data structure and explain the time/space trade-offs, noting that some queries (like most platforms) may require a scan or a maintained max-heap.

Pro tip: Mention that you would maintain a reverse index from genre to games and from platform count to games, and for the 'most platforms' query, either keep a running max or use a heap—this shows you think about update costs and scalability beyond just initial implementation.

1. Clarify requirements and assumptions

Ask about data size, update frequency, and whether queries are read-heavy or write-heavy. Confirm if 'most platforms' means the maximum count or all games tied for maximum.

2. Design the core data model

Define a Game class/struct with fields: name, releaseDate, platforms (list/set), genre, publisher, country (optional), discordServers (list). Store games in a primary collection, e.g., a list or map keyed by name.

3. Build auxiliary indexes for fast lookups

Create a map from game name to Game object for O(1) genre lookup. Create a map from genre to list of games for O(1) genre-based retrieval. Create a map from platform count to list of games for O(1) exact-N lookup.

4. Handle the 'most platforms' query

Maintain a variable tracking the maximum platform count and a list of games with that count, updating on insert/delete. Alternatively, use a max-heap or scan the platform-count map to find the highest key.

5. Analyze complexity and trade-offs

Discuss time/space complexity for each operation, and consider alternatives like sorted structures or caching if queries are frequent. Mention that maintaining indexes increases write cost but speeds up reads.

Key Points to Mention

Use of hash maps for O(1) average-case lookups on name and genre.
Maintaining a reverse index from genre to games to avoid scanning all records.
Using a map from platform count to games for exact-N queries, and a separate structure for max count.
Trade-offs between read-optimized indexes and write performance (e.g., updating indexes on insert/delete).
Handling optional fields (country) and multiple values (platforms, Discord servers) with appropriate data types (e.g., sets for platforms).
Edge cases: no games, ties for most platforms, N larger than any game's platform count.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.