Build Production-Grade Pipelines
Learn data engineering through real case studies with actual business problems, production architecture, and practical challenges.
PDF to Analytics Pipeline
Business Problem
Companies receive reports and documents as PDFs that need to be analyzed and integrated into their data warehouse.
Architecture
Data Flow
PDF Files → Azure Doc Intelligence → JSON → Azure Blob → Airflow → Databricks → DBT → Snowflake → Dashboards
Key Challenges
- Handling different PDF formats
- Parsing complex nested JSON
- Error handling and retries
Skills You Will Learn
Modern Data Warehouse Modeling
Business Problem
Raw data from various sources needs to be transformed into clean, reliable tables for analytics.
Architecture
Data Flow
RAW Layer → STAGING Layer → CERTIFIED Layer → CORE Layer → Analytics
Key Challenges
- Schema evolution
- Incremental processing
- Data lineage
Skills You Will Learn
Config-Driven Email Alerting System
Business Problem
Data teams need to monitor data quality and send alerts when issues are detected or when reports are ready.
Architecture
Data Flow
Config Tables → Airflow DAG → SQL Queries → Results → Email Templates → Delivery
Key Challenges
- Dynamic query generation
- Template management
- Error handling
Skills You Will Learn
YouTrack/API Data Pipeline
Business Problem
Project management data from APIs needs to be extracted, transformed, and loaded for analytics.
Architecture
Data Flow
API Endpoints → JSON → Azure Blob → Snowflake RAW → DBT Models → KPI Tables
Key Challenges
- API pagination
- Rate limiting
- JSON schema variations
Skills You Will Learn
Dashboard Automation Pipeline
Business Problem
Business stakeholders need automated, reliable dashboards that refresh on schedule with validated data.
Architecture
Data Flow
Source Data → DBT Models → Quality Checks → Dashboard Tables → BI Refresh → Alerts
Key Challenges
- Refresh dependencies
- Data freshness
- Quality gates