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Problem Solving and Scenario Analysis Questions

Candidates are expected to demonstrate a systematic, structured approach to analyzing and resolving technical and operational scenarios. This includes clarifying the problem statement, eliciting requirements, constraints, and assumptions, and identifying missing information or ambiguous areas. Candidates should decompose complex problems into logical components, prioritize tasks or evidence, generate solution options, and perform trade off evaluation that balances impact, feasibility, and risk. Core skills assessed include root cause analysis, incident diagnosis and forensic investigation, and evaluation of technical customer scenarios such as large scale migrations. Candidates should reason about data consistency and concurrency, security and authentication concerns, and payment and transaction flows when relevant. They should design test cases and acceptance criteria, propose instrumentation and monitoring for verification and observability, and identify opportunities for automation and operationalization. Clear communication of the recommended approach, expected outcomes, and the rationale for choices, including when to use a programming solution versus a query based approach, is essential.

HardTechnical
48 practiced
Feature computation joins a large event stream (1B rows/day) with a high-cardinality dimension table causing memory blowups in Spark. Describe optimization strategies: pre-aggregation, bloom filters, hyperloglog, partitioning, broadcast vs shuffle joins, and when to use each. Show which you'd try first and why.
MediumTechnical
48 practiced
A binary classifier's online accuracy drops by 8% after a scheduled retrain. Outline a systematic root-cause analysis plan: list the data, model, and infrastructure checks you would perform, the experiments you would run to isolate causes (dataset shift, label leakage, training bug), and how you'd prioritize remediation steps.
MediumTechnical
46 practiced
You must add support for multi-currency amounts to a payments database with 500k transactions/day, zero downtime, and accurate historical reporting. Describe a step-by-step migration plan: schema changes, data backfill, dual-writing, cutover, validation queries, and rollback strategy.
MediumTechnical
34 practiced
Design acceptance criteria and a testing suite for promoting a new fraud-detection model into production. Include dataset checks, metric thresholds, stress tests, guardrail metrics to avoid revenue loss, and how to run canary evaluations.
HardTechnical
40 practiced
Given the following simplified log excerpt:
2025-11-18T10:01:02Z TRACE tx=abc123 service=orders event=created2025-11-18T10:01:03Z ERROR tx=abc123 service=payments event=charge_failed code=INSUFFICIENT_FUNDS2025-11-18T10:01:03Z WARN tx=abc123 service=orders event=cancel_attempt reason=timeout2025-11-18T10:01:04Z ERROR tx=abc123 service=payments event=refund_failed code=DB_WRITE_ERR
Analyze the timeline, identify probable root causes, and propose immediate and long-term fixes to prevent similar failures.

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