Develop essential engineering skills with expert instruction and practical examples.
This comprehensive course is designed to help you master the key skills and concepts required to excel in data engineering technical interviews. You will learn core topics including relational and NoSQL databases, data warehousing models, and efficient data storage formats like Parquet and Avro. The course dives deep into data processing techniques such as ETL pipelines, big data tools including Hadoop and Apache Spark, as well as real-time data streaming technologies like Kafka and Flink.
Additionally, you will get hands-on experience with popular cloud platforms including AWS, GCP, and Azure, and learn best practices for workflow orchestration using tools like Airflow. Programming fundamentals in Python, Java, and Scala are covered alongside automation with Linux scripting and container orchestration using Docker and Kubernetes. The course also emphasizes data quality, security, and monitoring strategies to ensure reliable pipelines.
Finally, you will develop an understanding of system design and performance optimization techniques essential for building scalable and efficient data solutions. Whether you're preparing for your first data engineering role or looking to level up your career, this course will equip you with the knowledge and confidence to succeed in competitive job markets. Comprehensive exercises, real-world examples, and interview tips are included to maximize your preparation.
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