Collaboration and Business Impact Questions
Emphasis on how cross functional work produces measurable outcomes for teams and the organization. Topics include defining success metrics, describing how collaboration influenced product or business outcomes, driving adoption of solutions across teams, and demonstrating impact at team and organizational levels. Candidates should be able to articulate how collaborative efforts changed roadmaps, improved metrics, saved costs, increased revenue, or accelerated delivery.
MediumTechnical
0 practiced
Describe how you would collaborate with SRE and infrastructure teams to reduce ETL job failures: define joint responsibilities, metrics to track (failure rate, MTTR), changes to CI/CD and deployment processes, improvements to alerting, and how you would demonstrate impact to stakeholders after changes are made.
MediumTechnical
0 practiced
Design a concise runbook and escalation policy for a critical ETL job that feeds revenue dashboards. Include detection triggers, immediate mitigation steps (e.g., retries, backfills), who is on-call at each step, communication templates for stakeholders, and post-incident follow-up and timelines for RCA and fixes.
HardTechnical
0 practiced
Prepare an analysis comparing a managed streaming service (e.g., cloud-managed Kafka) charging $0.50/GB of throughput versus a self-managed Kafka cluster with estimated infrastructure cost X and ops cost Y. Outline the metrics to compare (TCO over 3 years, reliability, latency, operational risk, staffing), data sources for estimates, and how you would present a recommendation to executives including sensitivity to data growth.
HardSystem Design
0 practiced
Your leadership must choose between a centralized data platform team or federated ownership where each product team owns pipelines. Propose a decision framework with criteria (time-to-deliver, reliability, cost, compliance, innovation), trade-offs, a pilot approach, and success metrics you would use to recommend one model or a hybrid approach.
HardTechnical
0 practiced
With constrained engineering capacity, propose a prioritization framework for data platform improvements that aligns with company OKRs, includes stakeholder input, and yields measurable impact. Describe scoring criteria, cadence for reviews, governance for exceptions, and a communication plan to get buy-in from product and analytics leaders.
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