Data Engineering
Launch your career in Data Engineering. Build job-ready skills through hands-on projects and learn to work with industry-standard tools.
Duration
70+ Hours
Level
Beginner to Intermediate
Location
Onsite Training
What you'll learn
Course Content
Data Warehouse
Learn the fundamentals of data warehousing and cloud-based solutions
- • Data Warehouse Concept
- • OLAP vs OLTP
- • Data Modeling
- • Introduction to Google Cloud Provider (GCP)
- • BigQuery
Workflow Orchestration
Master the tools and techniques for orchestrating data workflows
- • Data Lake (GCS)
- • ELT vs. ETL
- • Apache Airflow
Deployment and Version Control
Learn best practices for code management and deployment
- • Dealing with git version control (GitHub)
- • Create Airflow Composer
- • Setup CI/CD for deployments (GCP Cloud Build)
Analytics Engineering
Transform raw data into analytics-ready models
- • DBT
Batch Processing
Process large volumes of data efficiently
- • Spark Dataframes
- • Spark SQL
Streaming
Build real-time data processing systems
- • Introduction to Kafka
- • Google Pub/Sub
Prerequisites
- Basic programming knowledge
- Understanding of SQL basics
- Problem-solving aptitude
Meet Your Instructors
A seasoned data leader who has built data teams and infrastructures from scratch at Klivvr, Soum and AnalyticaBI. With deep expertise in data engineering and analytics, he specializes in designing scalable data architectures and driving data-driven decision-making.
Experienced Data Engineering Manager with 12+ years in the data and IT industry, currently at Teradata, a leading company in cloud data analytics and enterprise solutions. Managing huge scale projects at different industries and government sectors.
An extinguished Data engineer focused on creating impactful solutions and fostering technical excellence. Experienced in modern development practices and passionate about teaching and mentoring with solid experience in data engineering and data management.
