As organizations migrate to the cloud, securing data pipelines and storage becomes paramount. This course focuses on the intersection of data engineering and security, teaching participants how to build resilient, secure, and compliant data architectures in cloud environments like AWS, Azure, and Google Cloud.

Course Objectives:

• Build secure and scalable data pipelines.
• Implement data encryption at rest and in transit.
• Manage access control in cloud-based data warehouses.
• Ensure data privacy and compliance within cloud infrastructures.
• Monitor and audit cloud data activities for security anomalies.

Target Audience:

• Data Engineers and Architects.
• Cloud Security Engineers.
• IT Professionals managing cloud migrations.

Course Outline:

Day 1: Cloud Architecture and Data Engineering Basics

• Overview of Cloud Service Models (IaaS, PaaS, SaaS).
• Shared Responsibility Model in Cloud Security.
• Designing Scalable Data Pipelines.
• Introduction to Modern Data Warehousing (Snowflake, BigQuery, Redshift).

Day 2: Securing the Data Lifecycle

• Data Classification and Sensitivity Mapping.
• Encryption Techniques: Symmetric vs. Asymmetric.
• Key Management Services (KMS) in the Cloud.
• Data Masking and Anonymization for Security.

Day 3: Access Management and Network Security

• Role-Based Access Control (RBAC) vs. Attribute-Based Access Control (ABAC).
• Securing Virtual Private Clouds (VPC) and Subnets.
• API Security and Gateway Management.
• Zero Trust Architecture for Data Access.

Day 4: Governance and Compliance in the Cloud

• Data Sovereignty and Residency Challenges.
• Managing Compliance (SOC2, ISO, GDPR) in Cloud Environments.
• Data Auditing and Logging Strategies.
• Disaster Recovery and High Availability for Data.

Day 5: Advanced Cloud Security & Automation

• Automating Security with DevSecOps.
• Using AI for Threat Detection in Data Streams.
• Managing Multi-Cloud Security.
• Final Case Study: Securing a Global Data Infrastructure.