Assess how candidates identify, prioritize, and resolve problems when faced with limited time, limited resources, changing requirements, or unclear information. This includes execution discipline to maintain delivery and unblock teams, pragmatic adaptation of designs or plans to meet constraints, handling ambiguity by making reasonable assumptions and iterating, communicating trade offs and risks to stakeholders, and demonstrating creative but practical solutions that preserve core quality objectives. It also covers applied troubleshooting for realistic business problems such as calculating retention cohorts, reconciling datasets of differing granularity, or debugging data quality and pipeline issues, with emphasis on clearly explaining approach, assumptions, and recovery steps.
HardTechnical
0 practiced
You discover intermittent data corruption in an ETL job that affects analytics and customer billing. Logging is limited for privacy reasons and corruption appears sporadic. As Solutions Architect, describe forensic steps to identify the root cause without exposing sensitive data, immediate mitigations to stop further corruption, a recovery plan for affected records, and long-term controls to prevent recurrence (checksums, schema validation, quarantine).
HardTechnical
0 practiced
Create a one-year migration plan to incrementally move a monolithic application to microservices with the objective of enabling faster delivery and without downtime. As Solutions Architect, describe decomposition strategy (bounded contexts), use of the strangler pattern, data migration approach (dual writes, anti-entropy), testing and release guardrails (feature flags, contract tests), team restructuring, and risk mitigation for rollback-free transitions.
MediumTechnical
0 practiced
An RFP requires a concise technical architecture and risk summary within 48 hours. As Solutions Architect, outline the one-page deliverable: key sections (architecture diagram, integrations, assumptions), a short risk register with mitigations, compliance callouts, and a prioritized list of unknowns you plan to validate in the kickoff. Explain how you would balance detail vs speed to instill confidence while being honest about risks.
MediumSystem Design
0 practiced
A third-party API begins rate-limiting you during peak user activity but your SLA requires continued operation. As Solutions Architect, design a fallback strategy that preserves core functionality: detail caching layers, request queueing/backpressure, adaptive backoff, degraded feature sets, and how you'd validate these mechanisms in a safe production-like environment.
HardSystem Design
0 practiced
Traffic is expected to jump 10x in two weeks due to a major campaign. You must propose the fastest feasible engineering changes to handle the spike: options include sharding the database, adding read replicas, aggressive caching, or autoscaling compute. As Solutions Architect, evaluate each choice for implementation speed, risk, capacity gain, and recommend an execution plan that minimizes user impact and rollback risk.
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