Data and AI

Building ETL and ELT Pipelines

Design and build the extract-transform-load pipelines that move data reliably from source systems into a usable warehouse

20h4 lessonsTier 2 hireabilityTier 2 certificate

What you'll be able to do

You can design and build both ETL and ELT pipelines, choose correctly between full and incremental loading strategies, and build pipelines with genuine monitoring and failure recovery built in from the start.

Job titles this qualifies you for

Data EngineerETL DeveloperData Platform Engineer
Market intelligence
Demand
High
Remote
72% remote roles
Nigeria salary
Not a primary local hiring category
Remote (USD)
$114,500–$137,500/year for the typical remote mid-level range (25th-75th percentile); average around $130,000-$148,000/year; senior remote data engineers average $191,822/year

Lessons

Stage 1 — Foundation
1
ETL Versus ELT: A Genuine Architectural Choice
35 min
2
Extraction Strategies: Full Versus Incremental
40 min
Stage 2 — Applied
1
Transformation Logic and Data Quality Checks
35 min
2
Monitoring and Recovering from Pipeline Failures
30 min
Tier 2 Proof Submission

ETL and ELT Pipelines Portfolio

Demonstrate genuine ETL/ELT architectural judgement, incremental extraction understanding, quality-check design, and monitoring/recovery discipline.

1.An ETL-versus-ELT scenario explanation with a realistic ETL-appropriate case
2.A high-water mark and delete-detection limitation explanation
3.Two differentiated data quality checks for a sales pipeline
4.Monitoring signals and a runbook entry for a specific failure scenario
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