interview-spark-iceberg-depth

Runs a role-play mock interview drilling Apache Spark and Iceberg internals with per-question feedback.

Updated May 31, 2026
One-click install
npx skills add https://github.com/noufal85/interview-skills --skill interview-spark-iceberg-depth-noufal85
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interview-spark-iceberg-depth
Source: https://github.com/noufal85/interview-skills/tree/main/netflix/skills/interview-spark-iceberg-depth
Command: npx skills add https://github.com/noufal85/interview-skills --skill interview-spark-iceberg-depth-noufal85

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Preparing for senior data-engineering technical screens requires realistic practice on Spark and Iceberg internals, but solo study lacks the pressure, probing follow-ups, and calibrated feedback of a real interview. ## Core Features & Use Cases - Live role-play mock interview: An interviewer persona (Staff DE or Senior IC) asks 8-12 questions mixing production scenarios (OOM at 3am, small-file explosions, traffic spikes) with direct internals questions (AQE, hidden partitioning, compaction, WAP). - Three drill modes: Spark-only, Iceberg-only, or Mixed, drawing from dedicated question banks in references/spark-questions.md and references/iceberg-questions.md. - Strict per-question feedback: Each answer is scored on correctness, depth, production realism, and trade-off awareness, with anti-patterns like tool_reflex and confident_wrong flagged. - Use Case: A senior DE candidate says "drill me on Spark and Iceberg" before a Netflix onsite; the skill runs a 45-60 minute mock, then delivers a final debrief with per-axis scores, top fixes, and knowledge-base gap updates. ## Quick Start Ask the assistant to start a mixed Spark and Iceberg mock interview using this skill and answer each question as it is posed.

Frequently Asked Questions about interview-spark-iceberg-depth

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I practice Spark and Iceberg interview questions with feedback?▼

Start the skill and pick Spark-only, Iceberg-only, or Mixed mode. The interviewer asks 8-12 questions from the bundled question banks and gives strict per-question feedback on correctness, depth, production realism, and trade-offs after each answer.

What topics does a Spark deep-dive interview cover?▼

The Spark question bank covers OOM scenarios, AQE internals, skew handling, shuffle optimization, the unified memory model, join strategies, caching, dynamic allocation, streaming watermarks, and cluster sizing, mixing production scenarios with direct internals questions.

What Iceberg topics should I prepare for a data engineering interview?▼

The Iceberg bank covers hidden partitioning and partition evolution, compaction strategies (bin-pack, sort, Z-order), WAP, schema evolution, snapshot expiration, concurrent-write conflicts, catalog choices, migrations, and incremental snapshot-based reads.

Can I run a mock interview without per-question feedback?▼

Yes. Say "exam mode" or "dress rehearsal" at session start to run a pure mock with no inline feedback. A full final debrief with per-axis scoring and top fixes still runs at the end.

How strict is the interview scoring rubric?▼

It uses a v0.4 strict senior-DE calibration: a correct-but-shallow answer scores Mixed, and a confident but technically wrong answer scores Weak. Strong requires correctness, one layer of depth, production realism, and a named trade-off threshold.

What happens if I don't know an answer during the mock?▼

Saying "I don't know" is treated as a calibration data point, not a failure. The interviewer gives a one-paragraph primer, and two concept gaps in one session switch the rest of the mock into study-companion mode.