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Problem Solving and Communication Questions

Assess a candidate's structured approach to solving problems and their ability to communicate their thinking clearly, regardless of whether the problem is technical, analytical, or business in nature. Look for: clarifying requirements and open questions before diving in, explicitly stating assumptions, breaking a complex or ambiguous problem into smaller components, proposing and comparing multiple approaches, explaining trade offs in plain language, narrating reasoning step by step as the work progresses, verifying a proposed solution (including edge cases, failure modes, or counterexamples), and adapting the approach when new information or constraints appear. Emphasis is on logical rigor, the ability to adjust the level of detail for different audiences (technical peers vs non-technical stakeholders), and continual communication so the interviewer can follow the candidate's reasoning and decisions throughout.

EasyTechnical
69 practiced
Implement in Python a simple deduplication function remove_duplicates(records) where each record is a dict with keys: 'id' (string), 'timestamp' (ISO string), and arbitrary payload. The function should keep only the latest record per id. Write your implementation and, while coding, narrate the trade-offs you consider around memory usage and streaming vs batch dedupe. Provide example input/output.
MediumTechnical
90 practiced
You're preparing a 5-slide proposal to convince engineering leadership to fund migration to a managed data warehouse. Outline the five main points you would include (benefits, risks, cost, migration plan, transition timeline) and what appendix data you'd bring to the meeting to support each point.
MediumTechnical
73 practiced
Given the table schema: events(event_id PK, user_id, event_type, occurred_at TIMESTAMP, payload JSONB). Write a SQL query (Postgres compatible) to deduplicate keeps latest event per (user_id, event_type) by occurred_at. Explain indexes, performance and how you'd run this on a 500M-row table without locking production reads.
EasyBehavioral
77 practiced
Behavioral: describe a time you missed a delivery deadline for a data pipeline. Use STAR: what caused the delay, how you communicated it to stakeholders, what mitigation steps you took, and what long-term changes you implemented to prevent recurrence.
HardSystem Design
82 practiced
Design a company-wide rollout for a new data contract system (schema registry + consumer-driven tests). Include the technical components (registry, CI checks, validation library), migration strategy for producers and consumers, enforcement model, monitoring/KPIs to track adoption and correctness, and a stakeholder communication/education plan.

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