Design a News Subscription Processing Engine
Design a durable engine that manages topic subscriptions and turns each published news item into the correct set of downstream deliveries.
Open practiceOptiver interview practice
Practice from 12 Optiver-tagged public coding problems, organized only by the stage, topic, difficulty, and recency metadata FastPrep can verify. The broader public catalog also includes 1 system-design exercise.
OA practice path
Build a timed implementation rhythm from prompt to edge cases. Problems are ranked by repeated public catalog sightings.
11 Optiver-tagged Online Assessment problems available.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
OPOptiver | Power Cell BankHash TableSorting | Hard | 6 public reportsLast reported Aug 2026 | Practice |
OPOptiver | Multi-Level Inventory Storage SystemDesignHeap | Hard | 5 public reportsLast reported Aug 2026 | Practice |
OPOptiver | Overheat Prevention ControllerSimulationDesign | Hard | 3 public reportsLast reported Aug 2026 | Practice |
OPOptiver | Construct Binary Tree S-ExpressionTreeParsing | Medium | 3 public reportsLast reported Jul 2026 | Practice |
OPOptiver | Days BetweenMathSimulation | Easy | 3 public reportsLast reported Jul 2026 | Practice |
OPOptiver | Count Bounded Share TransactionsDynamic ProgrammingCombinatorics | Medium | 1 public reportLast reported Aug 2026 | Practice |
OPOptiver | Count Ordered Size SequencesDynamic ProgrammingCombinatorics | Medium | 1 public reportLast reported Aug 2026 | Practice |
OPOptiver | Profitable Currency Exchange CycleDynamic ProgrammingGraph | Hard | 1 public reportLast reported Aug 2026 | Practice |
OPOptiver | Proportional Momentum Investment StatisticsArrayMath | Medium | 1 public reportLast reported Aug 2026 | Practice |
OPOptiver | Customer Checkout DurationDesignQueue | Medium | 1 public reportLast reported Jul 2024 | Practice |
OPOptiver | Print ScheduleGraphTopological Sort | Hard | 1 public reportLast reported Mar 2024 | Practice |
Phone practice path
Practice solving while explaining assumptions, tradeoffs, and complexity. Problems are ranked by repeated public catalog sightings.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
OPOptiver | Multi-Level Inventory Storage SystemDesignHeap | Hard | 5 public reportsLast reported Aug 2026 | Practice |
OPOptiver | Client Stock Position OperationsHash TableSimulation | Medium | 1 public reportLast reported Aug 2026 | Practice |
01 · Preparation plan
This page focuses on Optiver software-engineering practice. Its tree parser, position operations, and storage model form a concrete implementation path. Hiring activity remains on the separate insights hub, and this page deliberately avoids presenting mental-math tests or a particular online-assessment format as verified coverage. This is a suggested practice sequence, not the employer's interview process. Your invitation and recruiter guidance remain the source of truth.
Use S-expression construction to separate malformed input detection from output formatting. A graph that looks tree-like can still contain multiple parents or a cycle.
The client-position exercise is a state-update practice task. Derive command behavior from the prompt rather than assumptions about a real trading system.
The multi-level inventory exercise is useful for discussing movement, capacity, and lookup rules. A clear state model makes later optimizations easier to validate.
02 · Broader technical practice
These public Optiver-tagged exercises cover additional technical formats. They are included only when a verified catalog record and a crawlable practice page both exist.
Design a durable engine that manages topic subscriptions and turns each published news item into the correct set of downstream deliveries.
Open practice03 · Evidence boundary
It means practicing transferable implementation, testing, and technical reasoning with public catalog assets FastPrep tags to Optiver. It does not mean FastPrep has access to the company's assessments or any private interview bank.
Repeated public sightings and last-reported dates can help you prioritize practice, but they cannot predict the questions, format, or platform in a specific interview.
04 · Plain answers
This page owns technical-practice intent for Optiver. Hiring activity, timelines, and market signals remain on the separate hiring-insights page.
No. The evidence supports coding practice, not a dedicated mental-math or trader-test simulation. Use these assets for parsing, state, and algorithm reasoning. Consult your invitation for any separate numerical assessment and the hiring-insights hub for aggregate application activity.
No. FastPrep is an independent interview-preparation product and is not affiliated with Optiver. The page uses FastPrep's public practice catalog and does not claim official, private, leaked, or proprietary employer questions.
Stage labels come from FastPrep's public problem metadata. A problem can carry more than one reported stage, and hiring processes can change by role, level, location, and date. Treat the labels as preparation context, not a guarantee.
Start with the stage named in your invitation or recruiter message. If no stage is known, use the largest available set to build general problem-solving fluency, then rehearse explanation and testing separately.
No. Public catalog counts, stage tags, and last-reported dates can help prioritize practice, but they cannot predict a specific interview's questions, sequence, timing, or platform.
Your next stage, made concrete
Start with the stage named in your invitation, then use public evidence as context—not as a promise of what you will be asked.
Open the practice set