Easy-level cloud & tools questions from real data engineering interviews.
These easy cloud & tools 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 fundamentals — 28 easy, 0 medium, and 0 hard questions. Recurring themes are airflow, spark, and etl — these patterns appear most often in real interviews and reward the deepest preparation. These questions have been reported across 22 companies including EY and Capco. Average answer is around 1 minute of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 28 curated questions: 28 easy. There's a strong foundation of fundamentals-focused questions — ideal for building confidence before tackling advanced topics.
The most frequently tested areas in this set are airflow (4), spark (4), etl (4), sql (3), and python (2). Focusing on these topics will give you the highest return on your preparation time.
Start with the easy questions to warm up and solidify fundamentals. 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.
What are Airflow Operators? Give examples.
Explain the difference between Azure Data Factory (ADF) and Databricks.
How do you handle data security and compliance in a cloud environment?
What is Azure Data Factory (ADF), and what are its main components?
What is the role of the Integration Runtime (IR) in ADF?
Describe a scenario where AWS Data Pipeline is preferred over Glue. Why?
Describe an AWS EC2 instance and how IAM roles/policies enhance security.
Explain the role of Airflow DAGs in Cloud Composer.
Fabric pipelines vs. ADF pipelines
How Airflow stores logs and the role of its backend database
How do you copy all files from one source path to target in ADF?
How do you monitor and log data pipelines in AWS?
How do you secure data at rest and in transit for AWS RDS?
How does Azure Kubernetes Service (AKS) manage scaling and updates for containerized applications?
How does the trust relationship policy in IAM roles work?
How to copy all 1000 tables from source to target in ADF?
How would you handle a situation where an EMR cluster fails mid-job?
How would you pass data between Lambda functions in Step Functions?
Running multiple notebooks - dbutils.notebook.run()
S3 Storage Options: Describe Standard, Intelligent-Tiering, and Glacier.
Securing AWS Lambda: IAM roles, VPC integration, and security measures?
Types of Integration Runtimes (IR) - self-hosted, Azure, SSIS
What are Azure Blueprints, and how are they different from Azure Policies?
What are common issues faced with REST APIs in ADF, and how do you resolve them?
What are provisioned throughput and auto-scaling in DynamoDB?
What are the differences between %run and dbutils.notebook.run?
What are the differences between SSE-S3, SSE-KMS, and SSE-C encryption?
What are the limitations of AWS Glue and Lambda?
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