(Jan 2025 - Present)
Associate Data Engineer
Quantrail Data
Hey There!
I'm Mohamed Hussain S, a Data Engineer turning real-world problems into solutions with code and curiosity.
constcoder={name:'Mohamed Hussain S',skills:['Python', 'SQL (Advanced)', 'Bash (Basics)', 'ClickHouse', 'PostgreSQL', 'MySQL', 'Apache Airflow', 'Git & GitHub', 'VS Code'],hardWorker:true,quickLearner:true,problemSolver:true,hireable:function() {return(this.hardWorker&&this.problemSolver&&this.skills.length>=5);};};About Me
Driven by Curiosity, Fueled by Data
Associate Data Engineer focused on building and operating real-time data systems. I work with ClickHouse, Kubernetes, PostgreSQL, and modern infrastructure to design scalable pipelines, understand system internals, and deploy reliable data platforms.
Experience
(Jan 2025 - Apr 2025)
Final Year Project Developer
AutoTrend - Demand Prediction System
(Apr 2024)
Hackathon Team Lead
TechQuest - MedRem
Skills
PROJECTS
ClickHouse Metrics Extractor
constproject={name:'ClickHouse Metrics Extractor',tools: ['Python', 'Airflow', 'Docker', 'ClickHouse', 'clickhouse-connect],myRole:Intern Project | Automation & Monitoring,Description: Built an automated system to collect ClickHouse internal metrics every hour using Airflow. Stored results in daily CSV files using Docker containers and Python scripts. Helped practice metric monitoring, logging, and scheduled data capture.,};COVID-19 Data Pipeline
constproject={name:'COVID-19 Data Pipeline',tools: ['Python', 'Airflow', 'Docker', 'PostgreSQL', 'Requests],myRole:Intern Project | ETL & Scheduling,Description: Designed a complete data pipeline to pull COVID-19 stats from an API, process it, and store it in PostgreSQL. Used Airflow for orchestration and Docker for containerization. Focused on real-world ETL, retries, and modular scheduling.,};TrendLite - Live Retail Insights
constproject={name:'TrendLite - Live Retail Insights',tools: ['Python', 'Streamlit', 'ClickHouse', 'Altair', 'Pandas],myRole:Intern Project | ETL & Visualization,Description: Deployed a real-time sales dashboard using Streamlit and ClickHouse. Included dynamic date filters and visuals for KPIs like revenue trends, product performance, and category insights.,};AutoTrend - Demand Prediction
constproject={name:'AutoTrend - Demand Prediction',tools: ['Python', 'Streamlit', 'Scikit-learn', 'Pandas', 'YData Profiling],myRole:Capstone Project | Team of 2,Description: Created a no-code tool for demand prediction using AutoML. Included EDA, model selection, and ensemble-based prediction with a focus on user-driven configuration and visual results.,};Education
Oct 2021 - May 2025
B.E. Computer Science and Engineering
Rajalakshmi Engineering College, Chennai, India
Jun 2019 - May 2021
High School Diploma, Science Stream
International Indian School Jeddah, Saudi Arabia
Blogs
16
When Logs Aren't Enough: Using tcpdump to Debug Real Network Problems
4 Min Read
In my previous post, I wrote about a Linux routing issue that broke a deployment and caused repeated...
36
The Hidden Linux Routing Issue That Broke My Deployment
5 Min Read
The deployment should have taken a few minutes. The application was running, DNS was configured...
13
ClickHouse Duplicates: Clean Your Results vs. Clean Your Storage
3 Min Read
The word FINAL appears in multiple places in ClickHouse. Two of the most commonly confused examples...