Role Specific Job Understanding Questions
Covers familiarity with specific job families and titles and the typical responsibilities and challenges associated with them. Examples include customer success, project management, account management, business intelligence, operations, sales operations, and executive roles such as vice president positions. Candidates should show domain knowledge about daily tasks, common tools, stakeholder interactions, and specific outcomes expected in those named roles, and ask role specific questions about scope and priorities.
MediumTechnical
0 practiced
A stakeholder says the dashboard numbers don't match the ad-hoc query they ran. Walk through a methodical debugging process to reconcile the discrepancy, including checks for differing filters, timezones, joins, aggregation logic, data source versions, caching, and lineage.
EasyTechnical
0 practiced
Identify 6-8 core metrics you would track for a subscription-based SaaS product. For each metric, provide a precise definition (formula), explain why it matters for business health, and state which stakeholder(s) would care most about it (e.g., CFO, Head of Product, Sales).
HardTechnical
0 practiced
Describe how you would set up and run a cross-functional analytics council to standardize metrics, prioritize projects, and manage disputes between teams. Include meeting cadence, roles (chair, metric owners, stakeholders), decision-making rules, documentation standards, and how you'd escalate unresolved disagreements.
MediumTechnical
0 practiced
An executive requests a concise analysis explaining this quarter's sales drop. Describe the analysis plan: high-priority hypotheses to test, minimal data to fetch for a 15-minute executive brief, visualizations you'd prepare, and how you'd translate findings into recommended actions.
HardTechnical
0 practiced
Your organization plans to migrate analytics from SQL reporting on denormalized tables to an event-driven atomic-event lakehouse (e.g., Delta Lake or Snowflake with event ingestion). Outline the migration strategy: modeling changes, data contracts, impacts on downstream dashboards, validation steps, retraining needs for analysts, and rollback strategies if problems arise.
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