Quick Guide to Becoming AWS Data Engineer

Max Barker — Mon, 13 May 2024 18:09:35 +0000

📈 AWS Services for Data Engineers:

Certainly, here's the information presented in a more concise list format:

Simple Storage Service (S3):
- Object storage center for storing various types of data for future processing.
AWS Glue:
- Serverless service for writing ETL jobs in Python/Spark without managing servers.
Amazon Redshift:
- Fully managed data warehouse service for analyzing data using SQL and BI tools.
Amazon EMR (Elastic MapReduce):
- Managed big data platform for processing large datasets using open-source frameworks like Hadoop/Spark.
AWS Lambda:
- Serverless computing service for running quick scripts on specific triggers/events.
Amazon Athena:
- Ad-hoc query interface for running SQL queries directly on files stored in S3 buckets.
Kinesis:
- Real-time data processing service for analyzing and storing streaming data.
DMS (Data Migration Service):
- Simplifies data migration tasks, making data management easier.

If you want to work at the top startups out of San Fran and New York. Join our discord!
https://discord.gg/WKj3uz6sZZ

How to become an Azure engineer

Max Barker — Sat, 11 May 2024 20:52:08 +0000

Azure provides a wide array of services, but as a Data Engineer, focusing on mastering key ones is crucial for efficient data workflows.

🔍 Essential Azure Services for Data Engineers:

Sure, here's the information presented as a list:

Azure Blob Storage:
- Foundation for storing raw data of all types, from text files to large video files.
Azure Data Lake Storage (ADLS):
- Highly scalable and secure data lake functionality optimized for large-scale analytics workloads.
Azure Data Factory:
- Serverless integration service for creating data-driven workflows, essential for ETL processes.
Azure Synapse Analytics:
- Limitless analytics service merging enterprise data warehousing and Big Data analytics.
Azure HDInsight:
- Fully managed cloud service for handling massive data volumes, ideal for transitioning from on-premises Hadoop or Spark setups.
Azure Functions:
- Serverless compute service for running event-triggered code without managing infrastructure.
Azure Databricks:
- Collaborative Apache Spark-based environment seamlessly integrating with other Azure services, perfect for big data analytics.
Azure Stream Analytics:
- Real-time data processing platform for developing and executing analytics on multiple data streams.
Azure Data Migration Service:
- Fully managed service simplifying the migration of databases to Azure data services.
Azure Cosmos DB:
- Globally distributed, multi-model database service suitable for real-time operational analytics.
Azure Data Fabric:
- Unified data layer for managing and securing data across various sources, ensuring consistent access and management.

If you want to work at the top startups out of San Fran and New York. Join our discord!
https://discord.gg/WKj3uz6sZZ