Data and AI

Python for Data Engineering

Write production-oriented Python for moving and transforming data reliably, not exploratory analyst scripts

24h4 lessonsTier 2 hireabilityTier 2 certificate

What you'll be able to do

You can write Python scripts that reliably read from and write to files, databases, and APIs, handle errors and edge cases without silently failing, and organise code into genuinely reusable, testable modules rather than one long script.

Job titles this qualifies you for

Data EngineerAnalytics 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
Reading and Writing Files and Databases Reliably
45 min
2
Working with APIs and External Data Sources
40 min
Stage 2 — Applied
1
Error Handling and Pipeline Reliability
40 min
2
Organising Code into Reusable Modules
35 min
Tier 2 Proof Submission

Python for Data Engineering Portfolio

Demonstrate reliable file/database handling, API integration discipline, error-handling/idempotency judgement, and code organisation.

1.A parameterised-query security explanation and a batch-insert performance explanation
2.A pagination logic description and an API-key security explanation
3.A bare except: anti-pattern explanation and an idempotency requirement description
4.A refactored function breakdown with one specific test case
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