Python Practices in Data Engineering: Interview Highlights

Dive deep into the world of data engineering with Python! This comprehensive guide covers essential topics like handling large datasets efficiently, automating ETL pipelines, optimizing code performance, and ensuring data quality. Learn how to integrate Python with cloud platforms like AWS and Azure for scalable workflows, process real-time data streams using Apache Kafka and PySpark, and create compelling data visualizations for stakeholders. Discover best practices for writing efficient and maintainable Python code, debugging ETL pipelines, and managing data integration with tools like Snowflake Connector and SQLAlchemy. Perfect for aspiring and experienced data engineers, this interview-focused guide equips you with the knowledge and strategies to excel in Python-centric data engineering roles.

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