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Contributing

Thanks for helping improve Data Engineer Prep. This repo is meant to stay practical, curated, and interview-focused. Small fixes are welcome, and high-signal additions are even better.

Good Contributions

  • Typo fixes, broken-link fixes, and clearer explanations.
  • New quiz questions with concise answers.
  • Stronger examples for existing PySpark, SQL, data modeling, or AI-for-data-engineering topics.
  • Zephyr Coffee Co. scenario ideas that make a concept feel realistic.
  • Company interview patterns based on public sources or your own experience.
  • External resources with a short reason for why they are better than what is already linked.

Please Avoid

  • Random link dumps.
  • Self-promotional content.
  • AI-generated filler that has not been checked by a human.
  • Exact live interview questions copied verbatim.
  • Proprietary datasets, take-home assignments, internal rubrics, interviewer names, or confidential offer details.

The curation is the point. If a link, question, or explanation does not make the reader more prepared, leave it out.

Content Standards

Before opening a pull request, check that your change:

  • Is directly useful for data engineering interview prep.
  • Matches the existing tone: practical, direct, and no fluff.
  • Explains the "why", not only the "what".
  • Uses correct Markdown links and relative paths.
  • Avoids unsupported claims. If a fact depends on a source, cite it.
  • Keeps examples small enough to understand, but realistic enough to matter.

Adding Company Interview Content

Company interview pages are useful only when they are trustworthy. Please follow these rules carefully.

For community-sourced research:

  1. Copy company_interviews/_template_online.md.
  2. Use public sources only, such as GeeksForGeeks, Glassdoor, Reddit, Medium, YouTube, Naukri, or candidate blogs.
  3. Add a Sources section with actual URLs.
  4. Summarize patterns in your own words. Do not copy-paste from other sites.
  5. Prefer question patterns over exact wording.

For personal interview experiences:

  1. Copy company_interviews/_template_personal.md.
  2. Share round structure, topic areas, difficulty, prep strategy, and what the interview was testing.
  3. Do not include confidential or exact question text. Rephrase as a pattern.
  4. Include a "Delta from online.md" section if an online.md file exists for that company.

When in doubt, describe the type of question instead of the question itself.

Adding PySpark Notebooks

New notebooks should:

  • Be self-contained or clearly explain how to load any sample data.
  • Start with the business problem before the code.
  • Use the Zephyr Coffee Co. framing where it helps.
  • Include a walkthrough, at least one exercise, and a solution section.
  • Keep outputs clean before committing.
  • Include a Colab badge if the notebook is meant to run in Colab.

If you add a notebook, update the relevant module README and the root README.md if needed.

Adding Quizzes

Quizzes should use the existing collapsible Q&A style:

  • Start with basics.
  • Move into intermediate judgment.
  • End with senior/interview-style tradeoffs.
  • Keep answers short enough to review the night before an interview.

Pull Request Checklist

Before opening a PR:

  • Run a spell check or at least read the changed file end to end.
  • Click any new links you added.
  • Check that relative links work from the file's folder.
  • Make sure no private or confidential information is included.
  • Keep the PR focused. One topic per PR is easiest to review.

Review Philosophy

This repo values clear, battle-tested explanations over volume. A short correction that prevents someone from learning the wrong thing is a great contribution.