Twitter Interview Questions (2+ Questions)
Last Updated: June 23, 2026 • 2 Questions • Real Company Interviews
Prepare for your Twitter interview with our comprehensive collection of 2+ real interview questions and detailed answers. These questions have been curated from actual Twitter technical interviews across various roles including DevOps Engineer, Data Engineer, QA Engineer, and more.
Table of Contents
- Correcting Social Media Posts (easy)
- Post Engagement Trends (medium)
Our Twitter interview questions cover a wide range of technical topics and difficulty levels, from entry-level positions to senior roles. Each question includes detailed explanations and answers to help you understand the concepts and prepare effectively for your interview.
💡 Pro Tips for Twitter Interviews
- Practice each question and understand the underlying concepts
- Review Twitter's specific technologies and methodologies
- Prepare follow-up questions and edge cases
- Practice explaining your solutions clearly and concisely
Interview Questions & Answers
1. Correcting Social Media Posts
Spark is a big data framework that is designed to process massive amounts of data across multiple computers at the same time. Instead of tables, Spark uses data frames. We have one file, posts.csv. Its data frame contains seven columns: text of the post, ID, date, amount of likes, comments, and shares, and platform where it was published. We need to go through every post and replace the word Python with PySpark in the text column. withColumn is a data frame method that modifies or replaces a specific column. It takes two arguments. The first one is the column, it is the text column, and second one is the value that we want to add. For the second argument, we use regexReplace function. This function takes three arguments. The first one is the column to search. Second is the word to find. It is Python. And third is word to replace it with, which is PySpark.
2. Post Engagement Trends
SELECT
user_id,
post_date,
ROUND(
AVG(post_count) OVER (
PARTITION BY
user_id
ORDER BY
post_date ROWS BETWEEN 2 PRECEDING
AND CURRENT ROW
),
2
) AS rolling_avg_3d
FROM
posts
ORDER BY
user_id,
post_date;
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