Sabbir Hossain
Data Engineer at Bell Canada building scalable data infrastructure.
Former bioinformatics researcher at Johns Hopkins and University of Toronto. Harvard NCRC Plenary Speaker, back-to-back ASM ABRCMS award winner.
Who I Am
Data Engineer with a Research Background
TL;DR
- Data Engineer at Bell Canada (BBM — DE/AI), owning production ETLs and analytical systems on NTS — a multi-team, cross-functional platform
- Build and maintain data infrastructure, dashboards, visualization layers, and business-critical insights used by multiple internal teams
- University of Toronto Honours BSc (3.96 Major GPA) — CS + Bioinformatics Specialist
- Harvard plenary speaker (1 of 12 from 5,000+ applicants)
- ABRCMS Best Detailed Oral & Best Poster Award Winner (top researcher in division)
- 3+ years research across University of Toronto and Johns Hopkins
- Looking for Data, Platform, or Software Engineering roles
I'm a Data Engineer at Bell Canada under the Bell Business Markets (BBM) division, within the Data Engineering and Artificial Intelligence Team (DE/AI) where I architect and productionize mission-critical data pipelines on the Network Ticket Service (NTS) Platform. Before going full-time in industry, I spent 3+ years in computational biology research. I graduated from the University of Toronto (St. George Campus) with a 3.96 major GPA in Bioinformatics and Computer Science.
My research at UofT led me to cross-institutional work with Johns Hopkins, and eventually to present at Harvard — where I was selected as 1 of 12 plenary speakers from 5,000+ applicants. I won best presentation awards at ABRCMS in back-to-back years. Along the way, I processed 750+ TB of multi-omics data and realized that data engineering is where I belong — building the infrastructure that makes insights possible.
Data engineering sits at the intersection of software engineering and data science, and I love that. I care about distributed systems, platform engineering, data infrastructure, and creating elegant solutions to complex technical problems. Now I apply that same rigor from research to building enterprise-scale systems.
What I Love
Skills & Tools
Languages
Data & ML
Cloud & DevOps
Web & Databases
Analytics & Visualization
Methodology & Tools
Experience
Industry and research roles that shaped how I think about data. From building enterprise-scale pipelines at Bell Canada to processing 750+ TB of multi-omics data across top research institutions.
Industry
Research
Impact & Activity
Projects
Production systems and open-source tools I've built
NTS/MS Archway Pipeline@ Bell Canada
End-to-end ETL pipeline integrating 4 enterprise data sources into unified Control Plan reporting. 3-tier architecture processing 150,000+ records in ~20 minutes.
Duration Calculation Engine@ Bell Canada
Stateful Python algorithm computing 3 distinct duration metrics measuring agent work cycles. Two-pass group-by propagation model with zero calculation defects.
Data Quality Recovery System@ Bell Canada
Full-stack RCA diagnosing systemic data integrity drift. Staged recasts correcting 78,000+ records, expanding analytical coverage by 800%.
Microbiome Explorer
Interactive visualization platform for exploring microbial community data with taxonomic profiling, diversity analysis, and comparative metagenomics tools.
Bioinformatics Platform@ Johns Hopkins
Open-source full-stack bioinformatics platform with interactive D3.js visualizations, R Shiny dashboards, and real-time WebSocket data streaming. Private deployment at Johns Hopkins.
Let's Build Something Together
Looking for my next opportunity in data engineering or platform engineering.
