Technical Communication and Decision Making Questions
Focuses on the ability to explain technical solutions, justify trade offs, and collaborate effectively across engineering and non engineering stakeholders. Topics include articulating design decisions and their impact on reliability performance and maintenance, walking through solutions step by step, explaining algorithmic complexity and trade offs, asking clarifying questions about requirements, writing clear comments documentation bug reports and tickets, conducting and communicating root cause analysis, participating constructively in code reviews, and negotiating quality versus delivery trade offs with product and operations partners. Interviewers evaluate clarity of expression, reasoning behind decisions, and the ability to make choices that balance short term needs and long term quality.
EasyTechnical
0 practiced
Explain the structure of a concise root cause analysis (RCA) document for a production data pipeline incident targeted at both engineers and product managers. Include the key headings you would use (e.g., executive summary, timeline, impact, root cause, contributing factors, mitigation, action items, owners, verification plan) and describe the kind of content (metrics, logs, assumptions) that belongs under each heading.
MediumTechnical
0 practiced
A production pipeline is missing a column in 30% of daily reports. Draft a concise incident-update email to product and operations that includes: one-line summary, impact statement (who and what), current mitigation, next steps, ETA for a fix, where to find live updates, and a link to the ticket. Write the full email body you'd send.
HardTechnical
0 practiced
As a staff data engineer leading a cross-team decision on adopting a new data catalog, draft the decision memo comparing candidate tools on searchability, lineage capture, access control, metadata ingestion integrations, estimated migration effort, buy vs build analysis, and a rollout plan that minimizes disruption. Include KPIs you'd track to evaluate success after six months (e.g., adoption rate, time-to-find-dataset, number of stale datasets identified).
HardTechnical
0 practiced
You're the lead data engineer in charge of migrating an on-prem Hadoop platform to the cloud. Executives want minimal disruption and cost savings. Prepare a migration communication plan for engineering and non-engineering teams that covers phases (pilot, hybrid, cutover), decision criteria for lift-and-shift vs. re-architecture, rollback strategies, data validation approach, communication cadence, cost monitoring, and explicit success metrics to determine whether to proceed to the next phase.
HardTechnical
0 practiced
Draft a detailed plan to investigate intermittent data corruption discovered in ML training data. The plan should cover evidence collection (checksums, sample snapshots, timestamps), hypothesis prioritization, controlled tests to reproduce the corruption, safe rollback versus repair strategies, communication to data scientists about model retraining or rollback, and long-term preventive measures including monitoring and validation.
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