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
Compare blue-green and canary deployment strategies for data pipelines and platform services. Explain how each works, the pros and cons for stateful data jobs, impact on backfills and reprocessing, rollback characteristics, and give one concrete example of when to choose each strategy in a roadmap.
MediumSystem Design
0 practiced
Design a self-serve analytics platform enabling analysts to run ad-hoc queries and create dashboards while protecting platform stability and controlling cost. Include access controls, per-user or per-query quotas, sandboxing options, query routing/priority, cost tracking, and examples of enforcement mechanisms (e.g., query timeouts, resource pools).
EasyTechnical
0 practiced
Design a minimal but effective observability stack for ETL pipelines. Include components for logs, metrics, tracing, alerting, dashboards and lineage. Suggest concrete technologies (e.g., Prometheus, Grafana, OpenTelemetry, ELK, Data Catalog) and list what you would instrument on each ETL job (duration, read/write counts, error types, data volume, lineage metadata).
HardTechnical
0 practiced
Describe a comprehensive program to manage and retire technical debt in a large data platform. Cover how you identify debt (what metrics and signals), prioritize items (impact vs effort vs risk), schedule remediation work in roadmaps, assign ownership, incentivize teams to address debt, and how you prevent new debt from accumulating.
MediumTechnical
0 practiced
You inherit a monolithic collection of SQL scripts scheduled by cron. Propose a migration plan to convert them to modular DAGs using Airflow. Cover refactoring steps, parameterization, idempotency, data contracts, unit/integration testing, CI/CD deployment, secrets handling, and how you'd schedule the migration to reduce risk.
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