Major Technical Decisions and Trade Offs Questions

Behavioral and leadership oriented topic asking candidates to present real examples of significant technical decisions they influenced. Candidates should prepare two to three concrete examples that cover the problem context, options considered, reasoning and evaluation of trade offs, stakeholder engagement and buy in, the final decision, implementation approach, measured outcomes, and retrospective lessons including what they would do differently. This topic assesses ownership, influence, communication, cross functional collaboration, and ability to defend and learn from organizational level technical choices.

EasyTechnical

0 practiced

Describe a vendor selection you led for a specific component (e.g., monitoring, auth provider, data warehouse). List the evaluation criteria you used (technical, legal, financial), how you validated vendors (POC/trial, benchmarks), the trade-offs you documented, and how you executed onboarding for the chosen vendor.

HardTechnical

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In a geo-distributed service that requires localized low-latency reads and some globally consistent writes, choose a consistency model: eventual, causal, or strong. Explain how you mapped operations to consistency requirements, quantified business impact of anomalies, and designed mechanisms to enforce your chosen model in the implementation.

MediumTechnical

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Engineering requests you postpone addressing increasing technical debt to hit a major sales milestone. As the Solutions Architect, how do you balance short-term revenue targets against long-term product health? Present a decision framework, prioritization approach (quick wins vs foundational work), and an implementation plan that limits product risk while enabling the milestone.

MediumTechnical

0 practiced

During negotiation for a managed service contract, legal demands strict indemnities while engineering wants flexibility for version upgrades. How do you reconcile legal and technical requirements? Provide concrete clause language or compromise positions (e.g., service credits, phased upgrades, compatibility commitments) and describe the technical migration contingencies you would include.

MediumTechnical

0 practiced

A high-ingestion analytics pipeline uses a relational DB and struggles with ingestion spikes and storage cost. Walk through choosing between a write-optimized NoSQL store, sharding the relational DB, or introducing batching/streaming with message queues. Discuss data modeling, consistency guarantees, query patterns, cost and operational trade-offs.

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