Data Engineering Bootcamp
OLAP data warehouses from scratch. PySpark and PostgreSQL ETL pipelines. Star schema modeling. SCD2. Incremental loading. Graduates leave with a complete production-grade data infrastructure.
Curriculum
Detailed Syllabus
The Architecture Foundation
Understanding the Medallion architecture (Bronze, Silver, Gold) and implementing PostgreSQL as the source registry.
Compute & Orchestration
Deploying Airbyte for ingestion and Prefect for pipeline orchestration. Python-based custom connectors.
Lakehouse Logic
Introduction to Delta Lake and Spark. Partitioning strategies for high-concurrency environments.
Dimensional Modeling
Implementing Star Schema, Snowflake Schema, and SCD2 (Slowly Changing Dimensions) logic using dbt.
The Capstone Deployment
End-to-end deployment of a production-grade data pipeline for a real-world business scenario.
Admission Protocol
Pre-requisite: Basic Python/SQL knowledge.
Academic: BIT, BCA, MIT, or equivalent.
Commitment: 10-15 hours/week including labs.
Enroll in
Practitioner Training
Our bootcamps are high-intensity. We don't teach theory; we build practitioners ready for global production environments.
Candidate Admission Form
Applying for: Data Engineering Bootcamp