Databricks Architect
Learn advanced Databricks Architecture, Apache Spark, Delta Lake, Lakehouse design, distributed computing, data governance, and scalable enterprise data engineering solutions.
Course Description
The Databricks Architect Training Program is designed for professionals who want to build expertise in designing and implementing modern enterprise data platforms using Databricks.
Students will explore Databricks architecture, Apache Spark, PySpark, Delta Lake, Lakehouse architecture, Unity Catalog, data governance, and distributed data processing. The course covers advanced data pipeline design, medallion architecture, workload optimization, security, and performance tuning.
Learners will gain practical experience in designing scalable data platforms, integrating multiple data sources, managing enterprise data workflows, and implementing secure data solutions. Industry-oriented projects will help participants understand modern Lakehouse architecture and enterprise data engineering practices.
Trainer
N
Navdeep Singh
Data Analytics and Enterprise Data Architecture
20 years experience
Experienced Data Analytics Trainer with expertise in transforming raw data into actionable business insights. Skilled in data visualization, statistical analysis, business intelligence, and reporting....
Technologies Covered
Databricks
Apache Spark
PySpark
Delta Lake
Unity Catalog
Lakehouse Architecture
Medallion Architecture
Databricks SQL
Python
Advanced SQL
Structured Streaming
Data Governance
Data Security
Performance Optimization
Projects
- Enterprise Lakehouse Architecture Development
- End-to-End Medallion Data Architecture
- Real-Time Data Processing Platform
- Enterprise Data Governance Using Unity Catalog
- Large-Scale Data Pipeline Optimization
FAQ
Ans. A Databricks Architect designs scalable Lakehouse platforms, manages enterprise data architecture, establishes governance standards, and optimizes distributed data processing solutions.
Ans. Knowledge of Python, SQL, Apache Spark, data engineering, and cloud computing concepts is recommended.
Ans. Learners can explore roles such as Databricks Architect, Big Data Architect, Cloud Data Architect, Lakehouse Architect, and Senior Data Engineer.