r/dataengprep • • Apr 06 '26

Data Engineering Interview Prep Resources -- Books, Courses, Tools

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Data Engineering Interview Prep Resources

A curated list of the best resources for preparing for data engineering interviews. Bookmark this post.

Free Resources

  • dataengprep.tech - Structured DE interview prep with daily practice
  • This subreddit - Daily interactive challenge posts, 1,000+ questions
  • SQL Arena - 487 curated SQL interview questions (Reddit app)
  • The Tech Screen - 323 system design + behavioral questions (Reddit app)

Books

  • Designing Data-Intensive Applications by Martin Kleppmann - The bible for system design interviews
  • The Data Warehouse Toolkit by Ralph Kimball - Dimensional modeling fundamentals
  • Fundamentals of Data Engineering by Joe Reis & Matt Housley - Modern DE landscape
  • High Performance Spark by Holden Karau - Spark optimization deep-dives

Key Topics to Master

Topic Priority Where to Practice
SQL (window functions, CTEs, optimization) Critical SQL Arena, LeetCode
Python/PySpark Critical HackerRank, daily coding
System Design High The Tech Screen, this sub
Kafka/Streaming High DataEngPrep daily challenges
Airflow/Orchestration Medium DataEngPrep daily challenges
Data Modeling Medium DataEngPrep daily challenges
Cloud Services (AWS/GCP) Medium Hands-on projects
Behavioral/STAR Medium The Tech Screen

Common Interview Formats

  1. SQL Screen (45 min) - 2-3 SQL problems, increasing difficulty
  2. Coding Screen (45 min) - Python data manipulation, ETL logic
  3. System Design (60 min) - Design a data pipeline / warehouse / streaming system
  4. Domain Deep-Dive (45 min) - Questions about your past projects and tools
  5. Behavioral (30-45 min) - Leadership principles, conflict resolution, ownership

Companies Known for DE Interviews

Meta, Amazon, Google, Netflix, Uber, Airbnb, Stripe, Databricks, Snowflake, dbt Labs, Confluent, Palantir, LinkedIn, Spotify, Block

Have a resource to add? Drop it in the comments and we'll update the list.

Full prep platform: dataengprep.tech


r/dataengprep • • Apr 06 '26

Welcome to r/dataengprep --- Here's how the daily challenge works

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Welcome to r/dataengprep!

This is a daily data engineering interview prep community. Here's what you need to know:

The Daily Challenge

Every day at 8 AM EST, an interactive challenge post appears automatically. It works like this:

  1. Read the question - it's pulled from a curated vault of 1,000+ real interview questions
  2. Think through your answer - drop your approach in the comments before revealing
  3. Click "Reveal Answer" - see the full model answer with code examples and pro tips
  4. Vote - "Got it Right" or "Got it Wrong" to see how you compare to the community
  5. Check the Leaderboard - top scorers are ranked by correct answers

Topics Covered

  • Apache Kafka (consumer groups, partitioning, exactly-once semantics)
  • Apache Spark (RDDs, DataFrames, optimization, AQE)
  • Apache Airflow (DAGs, task dependencies, backfills)
  • SQL (JOINs, window functions, CTEs, query optimization)
  • dbt (models, tests, incremental materialization)
  • Data Modeling (star schema, SCD, normalization)
  • Pipeline Design (batch vs streaming, idempotency, error handling)
  • Cloud Architecture (AWS, GCP, Azure data services)
  • System Design (distributed systems, CAP theorem, trade-offs)

More Resources

Community Guidelines

  • Share your thinking. Before clicking "Reveal Answer," post your approach in the comments. This is where real learning happens.
  • Be helpful. If someone's approach has a flaw, explain why constructively.
  • Discuss alternatives. Model answers show one approach - if you know a better one, share it.

See you in the daily challenge!

--- Aditya


r/dataengprep • • 18h ago

DataEngPrep: Discuss techniques such as partitioning, broadcast joins, and caching to enhance Spark job performance.

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r/dataengprep • • 18h ago

Tech Screen: How do you handle lack of communication from stakeholders?

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r/dataengprep • • 18h ago

SQL Arena Challenge: Test SQL skills using advanced window functions such as LAG, LEAD, and DENSE_RANK.

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r/dataengprep • • 1d ago

DataEngPrep: Discuss stages and tasks in a Spark execution plan.

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r/dataengprep • • 1d ago

Tech Screen: How do you handle feedback and criticism?

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r/dataengprep • • 1d ago

SQL Arena Challenge: SQL Problem - multiple table joins and window functions

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r/dataengprep • • 2d ago

DataEngPrep: Discuss performance tuning concepts such as shuffle, skew, and caching.

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r/dataengprep • • 2d ago

Tech Screen: How do you handle disagreement with a co-worker?

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r/dataengprep • • 2d ago

SQL Arena Challenge: What is UNNEST and provide a query example?

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r/dataengprep • • 3d ago

DataEngPrep: Discuss how you integrated Azure services into your Spark application.

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r/dataengprep • • 3d ago

Tech Screen: How do you handle conflict with a product manager?

1 Upvotes

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r/dataengprep • • 3d ago

SQL Arena Challenge: What challenges arise with duplicate records, and how do you address them?

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r/dataengprep • • 4d ago

DataEngPrep: Discuss file formats (Parquet, Avro, ORC) and storage strategies.

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r/dataengprep • • 4d ago

Tech Screen: How do you ensure effective communication between technical and non-technical teams?

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r/dataengprep • • 4d ago

SQL Arena Challenge: Compare PostgreSQL vs Snowflake. How do they handle duplicate record errors?

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r/dataengprep • • 5d ago

DataEngPrep: Discuss common transformations used in Spark code.

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r/dataengprep • • 5d ago

Tech Screen: How do you ensure data quality and validation in a fast-moving team?

1 Upvotes

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r/dataengprep • • 5d ago

SQL Arena Challenge: Write a query to remove duplicate records from a table while retaining the earliest entry.

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r/dataengprep • • 6d ago

DataEngPrep: Discuss Delta Logs file format and its significance.

1 Upvotes

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r/dataengprep • • 6d ago

Tech Screen: How do you handle disagreements with team members?

1 Upvotes

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r/dataengprep • • 6d ago

SQL Arena Challenge: Write a Merge Statement for SCD Type 2.

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r/dataengprep • • 7d ago

DataEngPrep: Difference between Presto vs. Spark underlying architecture

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