Data Engineering with Databricks & Azure
Advanced Databricks training program focused on big data processing, Apache Spark, Azure Databricks, and modern data engineering workflows. Covers ETL pipelines, cloud integration with Azure, and real-world data projects with hands-on labs and live mentorship.
Created by
Pristient Orbit Team
Professional Certification Included
Successfully complete the Data Engineering with Databricks & Azure program to earn an industry-recognized certificate of completion.
Guaranteed Outcomes
People don’t buy lectures — they buy results.
Azure Data Engineering Project
Build and deploy a complete data pipeline using Azure Databricks, ADLS Gen2, and Azure Data Factory.
Live Mentorship
Hands-on training with expert support and real-time doubt resolution.
Industry Use Cases
Work on real-world big data scenarios aligned with enterprise environments.
Performance Optimization
Learn to optimize Spark jobs and manage cluster performance efficiently.
Specific Skills You'll Master:
Preview this Course
Training 5 or more people?
Get your team access to this course's top-rated content.
Pristine Orbit for BusinessTechnologies Covered
How You'll Learn
Live Interactive Sessions
Join expert-led classes via Zoom / Google Meet. Get your doubts cleared in real-time with direct mentor interaction.
Lifetime Recorded Access
Every session is recorded in HD. Get unlimited lifetime access to revisit complex concepts anytime, anywhere.
Hands-on Assignments
Practical learning via weekly assignments and industry-grade projects that build your professional portfolio.
Weekly Learning Cadence
A structured weekly roadmap designed to keep you on track. Consistency is built into our curriculum.
Meet Your Instructor
Pristient Orbit Team
Senior Technical Mentor
Learners
350+
Rating
4.6
Courses
5+
Professional Journey
7+ years of experience in big data engineering, Azure cloud integration, and analytics solutions
Tech Stack Expertise
Major Milestones
- Azure Data Pipeline Project
- Spark Data Processing
- Delta Lake Implementation
- Azure Databricks Deployment
Course Content & Outcomes
10 lectures • 6–8 Weeks total length
Build scalable data pipelines using Spark
Process large datasets with Databricks
Design and implement ETL workflows
Work with Delta Lake and modern data architectures
Deploy Databricks solutions on Azure cloud
Integrate Databricks with ADLS Gen2 and ADF pipelines
Implement secure access using Azure Active Directory
Optimize clusters and manage costs in Azure Databricks
Complete an end-to-end Azure-based data engineering project
Prepare for data engineering job roles
Requirements
- Basic understanding of programming concepts
- A computer with internet access
- No prior professional experience required
- Passion for learning and building!