How to Build an ETL Process
Create an extract, transform, load process that moves and reshapes data between systems reliably.
What You'll Learn
This intermediate-level guide walks you through how to build an etl process step by step. Estimated time: 14 min.
Step 1: Map source to target
Document source schemas, target schemas, and transformation rules for every data element in your pipeline.
Step 2: Build extraction logic
Implement full and incremental extraction patterns with change detection, watermarking, and schema validation.
Step 3: Implement transformations
Write transformation logic for data cleaning, type conversion, deduplication, enrichment, and business rule application.
Step 4: Create the load process
Build loading routines that handle upserts, deletes, and schema evolution in your target system.
Step 5: Add error handling and recovery
Implement dead letter queues for failed records, checkpoint-based recovery, and alerting for data quality violations.
Frequently Asked Questions
Should I build ETL or use a managed tool?▾
Use Fivetran or Airbyte for standard SaaS-to-warehouse ingestion. Build custom for unique sources, complex transformations, or real-time requirements.
How do I handle data quality in ETL?▾
Validate data at extraction, transformation, and loading stages. Implement row-level quality checks, track data lineage, and alert on quality metric degradation.
How do I make ETL idempotent?▾
Use upsert operations instead of insert, implement watermark-based incremental loading, and design transformations that produce the same output for the same input.