Technical Stack and Infrastructure Questions
Addresses the technology stack and platform infrastructure choices that support a product. Topics include cloud architecture, deployment platforms, service and data layer design, observability and monitoring, scalability and performance considerations, tooling for build and release, and assessing technical debt or modernization needs in the stack. Also covers evaluation of BI tools, ETL platforms, and how infrastructure choices affect team velocity and operational cost.
HardSystem Design
0 practiced
Design a data lineage and metadata management solution for a company with many data sources and BI tools. Describe required metadata (schemas, transformations, owners, freshness), tooling options (open-source or commercial), integration points (ETL, dbt, BI tools), and how you would surface lineage to report authors.
HardTechnical
0 practiced
A Redshift cluster is experiencing significant query queueing under high concurrency from dashboards. Propose architectural and operational remedies including workload management (WLM) tuning, concurrency scaling, read replicas or hot/fast clusters, separating hot datasets, and migrating heavy reports to extracts or a different warehouse.
HardTechnical
0 practiced
Design controls and processes to ensure GDPR compliance for a BI platform that stores and analyzes personal data. Cover data classification, minimization, pseudonymization or aggregation, access control, audit logging, consent management, retention/deletion workflows, and vendor assessments.
HardSystem Design
0 practiced
Design a CI/CD pipeline for dbt-driven data transformations. Include code review, unit and integration testing, ephemeral or dev environments, environment promotion, scheduling, secrets handling, rollback procedures, and coordination for schema migrations with downstream consumers.
MediumSystem Design
0 practiced
Design a deployment workflow for BI artifacts (data models, ETL code, dashboards, and automated data tests) across dev, staging, and production using Git and CI. Include how you manage environment-specific connections, secrets, approvals, schema migrations, and rollback procedures.
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