Interview Prep

A flashcard-style study app for data engineering interviews, covering Apache Spark, Kafka, Airflow, dbt, Databricks, AWS, Kubernetes, Terraform, system design, and behavioral questions.

Zero dependencies — no build step, no framework. Open index.html and study.

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Getting Started

Option 1 — Open directly

open index.html

Note: Browsers block fetch() on file:// URLs. If questions fail to load, use a local server (Option 2).

Option 2 — Local server (recommended)

npx serve .
# Open http://localhost:3000

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Question Schema

Each question file in data/ is a JSON array. Every entry follows this schema:

{
  "id": "spark-006",
  "question": "Your question here.",
  "answer": "Markdown answer. `inline code` and fenced blocks work.",
  "difficulty": "easy",
  "tags": ["tag1", "tag2"]
}

Field	Type	Values
id	string	Unique identifier (e.g. spark-006)
question	string	The question text
answer	string	Markdown-formatted answer
difficulty	string	easy, medium, or hard
tags	array	Arbitrary topic tags

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Adding Content

Add a question

Edit the relevant file in data/ and reload the page.

Add a category

1. Create data/{your-id}.json containing a JSON array of questions (schema above).
2. Register it in data/_categories.json:

   { "id": "your-id", "name": "Display Name", "icon": "🔥" }

3. Reload the page.

Generate personal questions

See personal-questions.md for instructions on generating interview questions tailored to your background.

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Deploying to GitHub Pages

1. Push the repository to GitHub.
2. Navigate to Settings → Pages.
3. Set Source to Deploy from a branch, branch master, folder /.
4. The app is fully client-side — no server configuration required.

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Progress Tracking

Study progress is persisted in localStorage under the key interview_prep. To reset all progress, clear your browser's local storage for the site.