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Data Engineering
Data Engineering: Building Robust Data Pipelines
Design and implement data pipelines. ETL processes, data warehousing, and modern data stack.
Ankit 15 min readFebruary 13, 2025
Data Engineering Fundamentals
Move, transform, and store data at scale.
Data Pipeline Types
ETL
- Extract, Transform, Load
- Traditional approach
- Schema-on-write
ELT
- Extract, Load, Transform
- Modern approach
- Schema-on-read
Tools
Orchestration
- Airflow
- Prefect
- Dagster
Processing
- Spark
- dbt
- Flink
Storage
- Data warehouses
- Data lakes
- Lakehouses
Best Practices
- Idempotent operations
- Data quality checks
- Monitoring and alerting
- Documentation
- Version control
Conclusion
Robust data pipelines are the foundation of data-driven organizations.
Data EngineeringETLData Pipelines
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