De' Clerke

IT graduate specializing in Kenyan data systems and automation. Expert in building efficient information pipelines with 55+ successful projects delivered using modern programming tools.

Nairobi, Kenya Joined on Sep 16, 2025 https://ian-mwendwa.vercel.app/

Education

Bachelor of Science in Information Technology (BSc. IT), Zetech University

Pronouns

he/him

Work

Intern

De' Clerke

Jun 7

I Shipped 12 BI Dashboards With 5 Different Tools. Here Is the Honest Comparison.

#dataengineering #python #datascience #sql

9 min read

De' Clerke

Jun 5

Machine Learning for Data Engineers: The Patterns I Actually Used Across 7 Projects

#python #machinelearning #dataengineering #datascience

11 min read

De' Clerke

Jun 2

FastAPI for Data Engineers: Building, Testing, and Debugging APIs That Don't Lie to You

#fastapi #dataengineering #testing #api

14 min read

De' Clerke

Jun 2

The Data Engineering Take-Home Assessment: How to Turn a 4-Hour Test Into a Job Offer

#dataengineering #career #sql #beginners

14 min read

De' Clerke

Jun 2

Data Engineering Interviews with No Industry Experience: A Playbook That Actually Works

#dataengineering #career #interview #python

22 min read

De' Clerke

Jun 2

SQL Interview Problems for Data Engineers: 30 Patterns That Actually Get Asked

#sql #dataengineering #career #interview

15 min read

De' Clerke

Jun 2

Terraform for Data Engineers: Provisioning GCS, BigQuery, S3, and Lambda Without Clicking Through Consoles

#devops #dataengineering #terraform #aws

11 min read

De' Clerke

Jun 2

Snowflake for Data Engineers: The Mental Model Shifts That Actually Matter

#snowflake #dataengineering #datawarehouse #database

9 min read

De' Clerke

Jun 2

PostgreSQL for Data Engineers: Indexes, Bulk Loads, and the Patterns That Actually Matter

#postgres #database #sql #psycopg2

13 min read

De' Clerke

Jun 2

Web Scraping Kenyan Data Sources: What's Available, What Fights Back, and the Patterns That Keep Pipelines Running

#webscraping #beautifulsoup #playwright #requests

12 min read

De' Clerke

Jun 2

GitHub Actions for Data Pipelines: The Setup I Use Across All My Projects

#cicd #githubactions #dataengineering #datapipelines

9 min read

De' Clerke

Jun 2

Python for Data Engineers: The Patterns I Use in Every Pipeline

#dataengineering #python #softwareengineering #tutorial

12 min read

De' Clerke

Jun 2

Kafka for Data Engineers: Core Concepts, KRaft, and the Patterns That Actually Work

#dataengineering #kafka #airflow #streaming

13 min read

De' Clerke

Jun 2

Linux for Data Engineers: From Zero to Production

#dataengineering #linux #beginners #wsl

22 min read

De' Clerke

Jun 2

# dbt in Production: 5 Gotchas That Broke My Pipelines

#dbt #dataengineering #elt #etl

7 min read

De' Clerke

Jun 2

5 Docker Compose Mistakes That Broke My Airflow 3 Setup 𖣘

#apacheairflow #dataengineering #orchestration #airflow3

5 min read

De' Clerke

Apr 15

Apache Airflow 2 vs 3: A Deep Technical Comparison for Data Engineers

#airflow #dataengineering #python #docker

15 min read

De' Clerke

Feb 4

⚡ High-Performance Warehousing: Partitioning & Clustering

#partitioning #clustering #datawarehouse #database

4 min read

De' Clerke

Feb 4

⭐ Star vs. ❄️ Snowflake: Designing the Data Warehouse

#datamodeling #starchema #snowflakeschema #dimensionalmodeling

3 min read

De' Clerke

Feb 4

🏦 OLTP vs. OLAP: Why One Database Isn't Enough

#datawarehouse #oltp #olap #database

3 min read

De' Clerke

Feb 4

🔄 ETL vs. ELT: The Evolution of Data Integration

#dataengineering #database #etl #elt

4 min read

De' Clerke

Sep 29 '25

Understanding Databases: SQL, NoSQL, Schemas,DDL, and DML

#database #backend #beginners #sql

4 min read

DEV Community

De' Clerke

Badges

Writing Debut

Skills/Languages

Currently learning

Currently hacking on

Available for

I Shipped 12 BI Dashboards With 5 Different Tools. Here Is the Honest Comparison.

Machine Learning for Data Engineers: The Patterns I Actually Used Across 7 Projects

FastAPI for Data Engineers: Building, Testing, and Debugging APIs That Don't Lie to You

The Data Engineering Take-Home Assessment: How to Turn a 4-Hour Test Into a Job Offer

Data Engineering Interviews with No Industry Experience: A Playbook That Actually Works

SQL Interview Problems for Data Engineers: 30 Patterns That Actually Get Asked

Terraform for Data Engineers: Provisioning GCS, BigQuery, S3, and Lambda Without Clicking Through Consoles

Snowflake for Data Engineers: The Mental Model Shifts That Actually Matter

PostgreSQL for Data Engineers: Indexes, Bulk Loads, and the Patterns That Actually Matter

Web Scraping Kenyan Data Sources: What's Available, What Fights Back, and the Patterns That Keep Pipelines Running

GitHub Actions for Data Pipelines: The Setup I Use Across All My Projects

Python for Data Engineers: The Patterns I Use in Every Pipeline

Kafka for Data Engineers: Core Concepts, KRaft, and the Patterns That Actually Work

Linux for Data Engineers: From Zero to Production

# dbt in Production: 5 Gotchas That Broke My Pipelines

5 Docker Compose Mistakes That Broke My Airflow 3 Setup 𖣘

Apache Airflow 2 vs 3: A Deep Technical Comparison for Data Engineers

⚡ High-Performance Warehousing: Partitioning & Clustering

⭐ Star vs. ❄️ Snowflake: Designing the Data Warehouse

🏦 OLTP vs. OLAP: Why One Database Isn't Enough

🔄 ETL vs. ELT: The Evolution of Data Integration

Understanding Databases: SQL, NoSQL, Schemas,DDL, and DML