My Data Engineer Interview Experience ----------------------------------------------------------------------------------- I recently interviewed for a Data Engineer role and wanted to share some of the topics and questions I came across. Hopefully, this helps anyone preparing for similar roles! 🔹 Python / Programming Difference between list, tuple, and set in Python How Python handles memory management and garbage collection Multithreading vs multiprocessing in Python Writing efficient Pandas operations for large datasets 🔹 SQL & Databases Write a query to find the nth highest salary in an Employee table Difference between OLTP and OLAP systems How indexes work in relational databases and when to use them Partitioning vs sharding in large datasets 🔹 Big Data & ETL Difference between batch and streaming data pipelines Kafka vs Kinesis: when to use each How Spark optimizes jobs under the hood (RDD, DataFrame, Catalyst optimizer) Best practices for building resilient ETL pipelines 🔹 Cloud & Data Warehousing Snowflake vs Redshift vs BigQuery: key differences How to design a data lake vs a data warehouse Role of IAM and data security in cloud environments How orchestration works with Apache Airflow 🔹 Coding Round Reverse words in a string without using built-in functions Implement a Kafka producer-consumer in Python Write an Airflow DAG for a daily ETL job Find duplicates in a dataset efficiently ----------------------------------------------------------------------------------- Hope this helps anyone preparing for their Data Engineer interviews! hashtag#DataEngineer hashtag#BigData hashtag#Python hashtag#SQL hashtag#ApacheSpark hashtag#Snowflake hashtag#Airflow hashtag#Kafka hashtag#ETL hashtag#InterviewPreparation hashtag#Coding

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