Introduction to the Course

Master the architecture and implementation of cloud-native data pipelines on leading platforms (AWS, Azure, GCP). This course focuses on modern, scalable, and cost-effective data solutions in the cloud.

Course Description

The future of data engineering is cloud-native. This comprehensive training explores how to design, build, and optimize data architectures leveraging the specialized services of major cloud providers. You will gain expertise in building Data Lakes and Data Warehouses using serverless computing, distributed processing, and modern ETL/ELT patterns. Through hands-on projects, you will master in-demand skills related to Cloud (AWS, Azure, GCP) data tools, making you job-ready for cloud-focused data engineering roles.

Course Content

The curriculum covers essential components and trends in cloud-native data engineering for 2025:

• Cloud Data Architecture Fundamentals:
  • Understanding Cloud-Native vs. Traditional Data Engineering
  • Data Lakes vs. Data Warehouses (and the Lakehouse concept)
  • Cloud storage services (S3, ADLS, GCS)
• Cloud-Specific Data Services:
  • AWS (Redshift, EMR, Glue, Athena, Kinesis)
  • Azure (Synapse Analytics, Data Factory, Databricks on Azure)
  • GCP (BigQuery, Dataflow, Dataproc, Pub/Sub)
• Real-time Data Processing and Streaming:
  • Building streaming data pipelines (e.g., Kinesis, Kafka, Pub/Sub)
  • Serverless data processing (e.g., AWS Lambda, Azure Functions)
• Data Transformation and Orchestration:
  • ETL/ELT processes in the cloud
  • Workflow automation (e.g., Apache Airflow on the cloud)
• DataOps and MLOps:
  • Applying DevOps principles to data pipelines
  • Monitoring, logging, and observability in cloud data environments
  • Data governance and security in the cloud

Why Choose Artiset and Our Training Methodology

• Platform Agnostic and Specific: We provide a holistic view of cloud-native concepts while offering deep dives into specific tools across major providers.
• Hands-On Expertise: Our training is heavily focused on hands-on projects that simulate real-world cloud deployments and data challenges.
• Expert Guidance: Learn from experienced cloud data architects and engineers who provide the mentorship needed to accelerate your career growth.

Benefits at the End of the Course

Upon completion, you will be able to:

• Design and implement scalable data architectures on cloud platforms.
• Utilize specialized cloud services for data storage, processing, and analysis.
• Build and manage real-time data pipelines and streaming solutions.
• Apply DataOps and MLOps principles to ensure reliable data workflows.
• Position yourself as a skilled Cloud Native Data Engineer in in-demand skills.

About the Trainer

Trainer is a seasoned Cloud Data Architect with more than 20 years of experience in Cloud Native Data Engineering across AWS, Azure, and GCP. Trainer possesses deep expertise in designing scalable Data Lakes and Data Warehouses, implementing complex real-time data pipelines. Trainer delivers hands-on training based on real-world projects, providing the expert mentorship necessary for participants to become job-ready in the cloud domain.