Portfolio Overview & Project Selection Questions
Be ready to describe your strongest 2-3 projects concisely. For each, explain the problem you solved, your design approach, tools used, and outcomes or learnings. Even if your projects are academic or hypothetical, focus on your thinking process and how you would measure success.
MediumTechnical
0 practiced
When sharing project details publicly or with external interviewers, how do you decide what to redact or omit (code, data samples, architecture) while still demonstrating technical credibility? Give concrete redaction strategies and examples for datasets and diagrams.
HardTechnical
0 practiced
Explain specific programs or processes you would start to scale best practices from your projects across teams (coding standards, CI/CD templates, standardized monitoring, data catalog adoption). Provide a phased rollout plan, success metrics, and how you would convince leadership to allocate time and budget.
MediumTechnical
0 practiced
For a project, explain how you collaborated with data scientists and product managers: how you gathered requirements, defined data contracts or SLAs, handled feature requests, and ensured reproducibility and discoverability of datasets for experiments. Provide an example of a conflict and how you resolved it.
MediumBehavioral
0 practiced
Tell the story of a schema change you encountered in production (added/removed columns, type changes, renamed fields). Explain how you detected the change, strategies you used for backward/forward compatibility, migration steps, testing plan, and rollback plan.
MediumTechnical
0 practiced
Describe how you'd present a performance-improvement story for a pipeline you optimized. What benchmarks would you run (throughput, latency, cost-per-unit), how would you visualize before/after results, and how would you attribute improvement to specific changes (partitioning, caching, code refactor)? Provide an example with hypothetical numbers.
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