Reddit Data Engineer interview questions & guide 2026

To help you prepare effectively, we have compiled representative questions based on real interview experiences at Reddit. These questions are grouped into core categories to help you identify patterns and focus your preparation on the areas that matter most.

SQL & Data Modeling

These questions evaluate your ability to write clean, efficient queries and design scalable data warehouse schemas.

• Given a table of user upvotes and downvotes, write a query to find the top trending subreddits based on activity velocity over the last 24 hours.
• How would you design a star schema for tracking user ad impressions and clicks across different platforms?

Preparing for an interview at Reddit requires a balanced approach. You must demonstrate strong software engineering fundamentals alongside specialized data engineering expertise. Reviewers look for candidates who can write production-grade code, design highly scalable systems, and collaborate effectively across teams.

SQL Mastery – You must be highly proficient in SQL. Interviewers will evaluate your ability to write complex queries, use window functions, optimize joins, and understand underlying execution plans. Brush up on data warehousing concepts, including normalization, denormalization, and partition strategies.

Algorithmic Problem-Solving – You need to write clean, runnable code during live coding sessions. Focus on mastering core data structures such as hash maps, trees, queues, and stacks. Be prepared to explain the time and space complexity of your solutions.

System Design & Scalability – You should be ready to architect large-scale data systems. You will be evaluated on your understanding of modern data technologies (e.g., Spark, Kafka, Airflow, Snowflake), batch versus streaming paradigms, and how to design fault-tolerant, cost-effective pipelines.

Collaboration & Ambiguity – You must show that you can thrive in a fast-paced environment. Reddit values engineers who take ownership, communicate clearly with non-technical stakeholders, and can navigate ambiguous problem spaces with a user-first mindset.

The interview process for a Data Engineer at Reddit is rigorous and designed to evaluate both your technical depth and cultural alignment. Candidates typically report a structured progression that begins with initial screening and culminates in a comprehensive virtual onsite loop.

The journey starts with a friendly conversation with a recruiter to discuss your background, your interest in Reddit, and basic role alignment. This is followed by a technical screen, which frequently focuses on core SQL concepts and live coding via a collaborative platform like Coderpad. If you pass this stage, you will move to the virtual onsite loop, which consists of multiple rounds covering system design, advanced coding, data warehousing concepts, and behavioral evaluations.

The visual timeline above outlines the typical stages of the Reddit hiring journey. Candidates should use this roadmap to pace their preparation, ensuring they master SQL and basic algorithms before the technical screen, and save deep-dive system design practice for the onsite loop. Note that while the flow is standardized, the specific focus of technical rounds can occasionally shift depending on whether the team leans more toward data warehousing or infrastructure engineering.

To succeed at Reddit, you must perform consistently across several core technical domains. Below is a detailed breakdown of what to expect and how to demonstrate mastery in each key area.

SQL & Data Warehousing

SQL is a foundational skill for any Data Engineer at Reddit. You will face dedicated rounds testing your ability to manipulate large datasets and design clean, efficient schemas that support analytical use cases.

Be ready to go over:

• Analytical Window Functions – Mastering functions like ROW_NUMBER(), RANK(), LEAD(), LAG(), and running totals.
• Data Modeling Paradigms – Designing star schemas, snowflake schemas, and understanding when to use slowly changing dimensions (SCDs).
• Query Optimization – Identifying performance bottlenecks, understanding indexing, partitioning, and clustering in modern cloud warehouses.
• Advanced concepts (less common) – Incremental table updates, materialization strategies, and handling complex nested JSON data in SQL.

Example questions or scenarios:

• "Design a schema to track user interactions with subreddits, including visits, posts, and comments, optimizing for daily active user (DAU) reporting."
• "Write a query to find the top 3 most popular posts in each subreddit for every hour of the day."

Coding & Systems Programming

Reddit expects its data engineers to write high-quality, maintainable code. You will participate in live coding sessions where you must solve algorithmic challenges and design custom data structures.

Be ready to go over:

• Data Structure Design – Creating custom classes and objects that meet specific time and space complexity requirements.
• File and Stream Processing – Writing memory-efficient code to parse, filter, and aggregate large text files or streaming payloads.
• Error Handling & Testing writing robust code that handles edge cases, null values, and malformed inputs gracefully.
• Advanced concepts (less common) – Multi-threading, concurrency, and custom generator patterns in Python.

Example questions or scenarios:

• "Using Coderpad, design a class that acts as a custom queue with a built-in deduplication mechanism."
• "Implement an algorithm to merge multiple sorted streams of log data into a single sorted output stream."

Data Systems Design

This round tests your ability to architect end-to-end data systems at scale. You will be given a high-level prompt and asked to design a solution, making trade-offs between latency, cost, and complexity.

Be ready to go over:

• Batch vs. Streaming – Choosing between technologies like Spark and Flink based on the real-time requirements of the business.
• Message Broking & Ingestion – Designing reliable ingestion layers using Kafka or Kinesis, including partition strategies.
• Orchestration & Lineage – Structuring complex DAGs in Airflow and ensuring data quality checks are built-in.
• Advanced concepts (less common) – Backpressure management, exactly-once processing semantics, and schema evolution.

Example questions or scenarios:

• "Design a real-time system to detect and flag spam comments across all of Reddit within 5 seconds of creation."
• "Architect a pipeline to ingest 10 billion events per day from mobile clients, process them, and load them into a data lake for ad-hoc analysis."

As a Data Engineer at Reddit, your primary focus will be on building and maintaining the infrastructure that makes data reliable and accessible. You will spend your days designing robust data pipelines, optimizing existing workflows, and ensuring the absolute integrity of Reddit's data assets.

You will collaborate closely with cross-functional partners, including Data Scientists, Machine Learning Engineers, and Product Managers. For instance, when a new feature is launched in a subreddit, you will partner with the product team to define the tracking events, build the pipelines to ingest those events, and model the final tables that data scientists use to evaluate the feature's success.

Additionally, you will drive initiatives to improve platform efficiency. This includes migrating legacy pipelines to modern distributed frameworks, optimizing storage formats to reduce cloud spend, and implementing automated data quality monitoring tools to catch anomalies before they impact downstream dashboards or machine learning models.

To be competitive for a Data Engineer position at Reddit, you need a strong background in software engineering combined with specialized big data expertise. The hiring team looks for candidates who have experience managing data at scale and can write production-grade code.

• Must-have technical skills – Strong proficiency in Python, Scala, or Java; expert-level SQL skills; hands-on experience with distributed computing frameworks like Apache Spark; and experience with orchestrators like Apache Airflow.
• Nice-to-have technical skills – Experience with streaming technologies like Apache Kafka or Flink; familiarity with modern cloud data warehouses like Snowflake or BigQuery; and experience with infrastructure-as-code tools like Terraform.
• Experience level – Typically 3+ years of professional experience in data engineering or software engineering roles, with a proven track record of designing and scaling production data pipelines.
• Soft skills – Excellent communication skills, the ability to translate technical concepts for non-technical stakeholders, and a proactive, self-motivated approach to solving ambiguous problems.

Q: How difficult is the Data Engineer interview at Reddit? A: The interview is generally rated as average to difficult. The coding and SQL rounds are highly practical but require solid preparation, while the system design round expects you to understand real-world scaling challenges at a deep level.

Q: What coding languages can I use during the technical rounds? A: You can generally write your solutions in any language you are comfortable with, though Python and Scala are highly recommended because they are the primary languages used within Reddit's data engineering teams.

Q: How long does the entire interview process take? A: The process typically takes between 3 to 6 weeks from the initial recruiter screen to the final decision, depending on scheduling availability and team alignment.

Q: Does Reddit offer remote work options for Data Engineers? A: Reddit has a highly flexible working model, offering remote, hybrid, and in-office options depending on your location and the specific team you are joining.

To maximize your chances of success, keep these practical, insider tips in mind as you prepare for your interviews:

• Master the Coderpad environment – Practice writing clean, runnable code without relying on IDE auto-complete. Be comfortable debugging your own syntax errors quickly under pressure.
• Focus on SQL window functions – Do not overlook your SQL preparation. Many candidates fail the technical screen because they struggle with complex analytical SQL questions, even if their general programming skills are strong.
• Always design for scale – When answering system design questions, never assume a small dataset. Always frame your solutions around handling petabytes of data, high concurrency, and distributed system failures.
• Be proactive with your recruiter – The scheduling process can occasionally experience delays. If you do not hear back within a few days of an interview round, send a polite follow-up email to keep the process moving.
• Understand Reddit's product – Spend some time using Reddit. Think about how features like subreddits, upvotes, karma, and comments translate into data events, and how you would model those events as a data engineer.

A Data Engineer role at Reddit offers an incredible opportunity to work on some of the most challenging and interesting data problems in the tech industry today. You will build systems that process massive user activity streams, directly influencing how millions of people discover and interact with communities online.

To succeed, focus your preparation on mastering SQL optimization, writing clean and modular code, and practicing end-to-end data system design. Remember to approach your behavioral rounds with a collaborative, user-first mindset, showing that you can navigate ambiguity and build strong partnerships across engineering and product teams.

The salary data above outlines the competitive compensation packages offered to engineers at Reddit. When reviewing these figures, remember that total compensation typically includes a base salary, equity components, and performance bonuses. Your specific offer will depend on your experience level, location, and performance throughout the interview loop.

With focused preparation, you can confidently navigate Reddit's rigorous interview process. For more real-world interview insights, detailed company guides, and interactive preparation resources, explore Dataford to give yourself the competitive edge you need to land your dream role.