RoadMap - Data Engineering

 Referred Link - https://www.linkedin.com/posts/manisha-lodha-b72713200_data-dataengineering-activity-7214909727208574976-vYhj

Navigating data engineering can be daunting, but with the right roadmap, it becomes a structured and achievable goal. Check out this comprehensive roadmap which breaks down the essential steps to becoming a proficient data engineer.

☑ Learn Programming: Start with foundational languages like SQL, Python, Java, and Scala. These skills are crucial for writing efficient data manipulation and processing scripts

☑ Processing: Understand batch and stream processing using tools like Spark, Hadoop, Flink, and Kafka. This knowledge is key to handling large-scale data workflows

☑ Databases: Get familiar with both SQL databases (MySQL, Postgres, Oracle) and NoSQL databases (MongoDB, Cassandra, Redis). Each has its unique advantages for different data scenarios

☑ Message Queue: Learn about message queues like Kafka and RabbitMQ to handle real-time data streams and communication between services

☑ Warehouse: Dive into data warehousing solutions such as Snowflake, Hive, Redshift, Synapse, and BigQuery to manage and analyze large datasets effectively

☑ Cloud Computing: Gain expertise in cloud platforms like AWS, Azure, and GCP, which are essential for scalable and flexible data infrastructure

☑ Storage: Explore different storage solutions like HDFS, S3, ADLS, and GCS. Understanding storage options is critical for efficient data management

☑ Data Lake: Learn about data lakes with tools like Databricks and Snowflake to store vast amounts of raw data in its native format

☑ Orchestration: Master orchestration tools like Airflow and Data Factory to automate and manage complex data workflows

☑ Resource Manager: Familiarize yourself with resource managers like YARN and Mesos to efficiently allocate resources in a distributed computing environment

Tags:

#DataEngineering, #Data