Project Deep Dives and Technical Decisions Questions
Detailed personal walkthroughs of real projects the candidate designed, built, or contributed to, with an emphasis on the technical decisions they made or influenced. Candidates should be prepared to describe the problem statement, business and technical requirements, constraints, stakeholder expectations, success criteria, and their specific role and ownership. The explanation should cover system architecture and component choices, technology and service selection and rationale, data models and data flows, deployment and operational approach, and how scalability, reliability, security, cost, and performance concerns were addressed. Candidates should also explain alternatives considered, trade off analysis, debugging and mitigation steps taken, testing and validation approaches, collaboration with stakeholders and team members, measurable outcomes and impact, and lessons learned or improvements they would make in hindsight. Interviewers use these narratives to assess depth of ownership, end to end technical competence, decision making under constraints, trade off reasoning, and the ability to communicate complex technical narratives clearly and concisely.
MediumSystem Design
47 practiced
Describe how you'd implement feature flags and canary releases for new dashboard features or metric changes. Include rollout patterns, telemetry to monitor impact (both performance and correctness), rollback criteria, coordination with product and SRE, and safeguards to prevent canary-induced incorrect metrics from leaking to executives.
MediumSystem Design
42 practiced
Design a BI reporting architecture to serve 1,000 concurrent dashboard users with occasional bursts to 10,000 within minutes. Describe the components (frontend, metrics API, cache/pre-aggregation layer, worker pools), how you'd handle concurrency and backpressure, graceful degradation of features under load, and your approach to capacity planning and load testing at that scale.
MediumTechnical
80 practiced
How would you design row-level security (RLS) and attribute-level access control for BI dashboards that must enforce different access policies across business units and geographies? Discuss policy definition, enforcement location (BI tool vs metrics API vs semantic layer), scalability, testing, auditing, and the user experience when permissions prevent viewing a metric.
MediumSystem Design
60 practiced
Design a BI dashboard system supporting multiple regions where some customers require that their data remain in-region for compliance. Outline architecture options (regional clusters, selective replication, separate tenants), routing and DNS strategies, failover, consistency implications for cross-region aggregates, and how you'd handle customers that require cross-region reporting.
MediumTechnical
81 practiced
Walk through a migration plan from an on-prem BI stack to a cloud SaaS BI platform. Cover discovery and inventory of artifacts, evaluating feature parity, secure data access patterns, cutover strategies (big-bang vs parallel-run), validation and reconciliation, rollback plans, governance, training, and how to handle decommissioning of the old platform.
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