Hard-level general questions from real data engineering interviews.
These hard general questions are selected from real interviews at top companies. Each question includes a detailed expert answer and pro tip to help you nail your interview. This set leans toward senior-level depth (25 of 25 are tagged hard). Recurring themes are spark, partition, and snowflake — these patterns appear most often in real interviews and reward the deepest preparation. These questions have been reported across 23 companies including Aarete and Dunnhumby. Average answer is around 2 minutes of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 25 curated questions: 0 easy, and 25 hard. The distribution skews toward harder problems, reflecting the depth expected in senior-level interviews.
The most frequently tested areas in this set are spark (10), partition (8), snowflake (6), sql (6), etl (5), and optimization (5). Focusing on these topics will give you the highest return on your preparation time.
Hard questions often appear in senior and staff-level rounds; attempt them after you're comfortable with the basics. For each question, try answering before revealing the solution. Use our AI Mock Interview to simulate real interview conditions and get instant feedback on your responses.
Have you worked on Data Warehousing projects?
Retrieve the most recent sale_timestamp for each product (Latest Transaction).
What is the difference between OLTP and OLAP?
Command to Read JSON Data and Options
Compare batch processing and stream processing for financial data.
Count occurrences of a specific word in a file
Data Security in BFSI - encryption, IAM, auditing
Data Storage and Retrieval Optimization techniques
Describe the ZS projects you worked on
Explain your project and the technologies used so far.
Find orders exceeding $1,000 in the last 30 days.
Highlight the tools and technologies you've used in your current project
How do these transformations impact memory usage?
How would you handle large datasets in a distributed computing environment?
How would you model customer transaction data for both analytical and operational use cases?
How would you model hierarchical data in a relational database?
Integrating an API with a Database - Steps
Synchronization Mechanisms
TCP vs UDP Protocol
Tell us about your technical experience?
Walk me through your resume. What are the key highlights that align with this role?
What are the different data sources you have used?
What are your strengths, and how do they align with the Data Engineer role?
What is PCollection?
What is your data volume?
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