Technical Vision and Infrastructure Roadmap Questions

This topic assesses a candidate's ability to define a multi year technical vision for infrastructure, platform, and systems and to translate that vision into a practical execution roadmap. Core skills include evaluating technology choices and architecture evolution, planning migration and modernization paths, anticipating scalability and capacity needs, and balancing cost performance with resilience and operational reliability. Candidates should demonstrate approaches to managing technical debt, sequencing investments across quarters and releases, estimating resources and timelines, establishing measurable infrastructure goals and key performance indicators, and implementing governance and standards. Discussion may also cover reliability and observability, security and compliance considerations, trade offs between short term stability and long term rearchitecture, prioritization to enable business outcomes, and communicating technical trade offs to both technical and non technical stakeholders.

EasyTechnical

0 practiced

You need to prioritize a backlog of BI infrastructure work with items like 'improve ETL failure alerts', 'migrate dashboards to new tool', 'optimize large query', and 'add dataset catalog'. Describe a prioritization framework you would use, how you'd score items, and how you'd defend your prioritization to stakeholders.

EasyTechnical

0 practiced

Define observability in the context of BI infrastructure. Identify the key telemetry signals (metrics, logs, traces, synthetic checks) you would collect for dashboards, report generation, and ETL pipelines, and explain how each signal helps with troubleshooting and capacity planning.

MediumSystem Design

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Draft a governance and metadata strategy to ensure discoverability, ownership, and access control for datasets used by BI. Include the role of a data catalog, lineage tracking, automated quality checks, and how enforcement would be integrated into the platform.

HardSystem Design

0 practiced

Propose an end-to-end disaster recovery strategy for BI infrastructure covering the data warehouse, ETL pipelines, dashboard metadata, and SLA for recovery time objective (RTO) and recovery point objective (RPO). Include failover mechanisms, testing cadence, and cost considerations.

EasyTechnical

0 practiced

Describe the main trade-offs between using a managed cloud analytics service (e.g., BigQuery, Snowflake) versus running a self-managed data warehouse (e.g., Postgres, Presto on VMs) for BI workloads. Consider cost, operational overhead, performance characteristics, security, and vendor lock-in.

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