Experience

  1. Data Engineer I

    Dhaka, BangladeshNEXT VenturesNEXT Ventures is a global fintech group specializing in propriatery trading and brokerage services headquartered in Dubai, UAEVisit website

    • Incoming Executive Data Engineer building scalable and intelligent data driven systems to address real business problems.

  2. Undergraduate Researcher

    Toronto, ON, CanadaCenter for Vision Research - York UniversityThe Centre for Vision Research (CVR) at York University pursues world-class, interdisciplinary research and training in visual science and its applications.Visit website

    • Secured $20,000 in research funding to build generative models using Python, support publication of computer vision paper in IJCV journal, and present findings at the university’s AI conference.
    • Used R to analyze and visualize research data for bi-weekly supervisor meetings and monthly lab progress presentations for a cross-disciplinary audience.
    • Implemented CI/CD pipelines in GitHub to automatically tag releases, version datasets, and assign DOIs through Zenodo.

  3. Data Engineer (Co-op)

    Toronto, ON, CanadaSanofiSanofi is a global pharmaceutical and healthcare company headquartered in France.Visit website

    • Maintained ETL/ELT pipelines, helped migration efforts from on-premise to AWS cloud, wrote automation scripts in Python and built Power BI dashboards to support data management and monitoring of vaccine manufacturing process.
    • Set up Spark ingestion pipelines and data governance practices for an S3 data lake, enabling cross-functional teams of data scientists, business analysts, and other stakeholders to access data more easily.
    • Used SQL and DAX to query and transform data directly from the data warehouse, ensuring Power BI dashboards provided consistent and up-to-date data across teams.
    • Reviewed and clarified Standard Operating Procedures (SOPs) and documentation for non-technical operators based on pharmacovigilance guidelines, helping ensure accurate and compliant data handling.
    • Used Atlassian Confluence to document API endpoints, CI/CD and data pipelines, helping future interns understand the systems and become productive more quickly.

Projects

DevTube Analytics Platform(opens in a new tab)

  • Python
  • FastAPI
  • RAG
  • AWS S3
  • Apache Iceberg
  • dbt
  • DuckDB
  • Dagster
  • Terraform
  • Built a Python and YouTube API pipeline that ingests video, creator, and engagement data into S3 and Apache Iceberg, creating a reliable historical dataset for tracking how technology content evolves over time.Built a Python and YouTube API pipeline that ingests video, creator, and engagement data into S3 and Apache Iceberg, creating a reliable historical dataset for tracking how technology content evolves over time.
  • Used DuckDB, dbt, and Dagster to transform and analyze the data with SQL, combining engagement, recency, viewing velocity, and cross-channel activity to identify trending videos, topics, and creators.
  • Built an AI-powered search interface with FastAPI, Qdrant, and RAG, using embeddings to retrieve relevant video transcripts and descriptions so users can ask natural-language questions about technology trends and trace answers back to their sources.

Pople - Distributed Quantum Chemistry Job Queue(opens in a new tab)

  • Python
  • FastAPI
  • Svelte
  • Typescript
  • ORCA
  • PostgreSQL
  • Websockets
  • Built a real-time dashboard using Svelte, TypeScript, JavaScript, HTML, and CSS to monitor quantum chemistry calculation jobs, allowing researchers to track progress without manually reading log files.
  • Built an async worker using Python, FastAPI, and PostgreSQL to orchestrate long running simulations directly from the web app instead of the terminal streamlining the computational chemistry workflow.
  • Implemented RESTful APIs and WebSockets to provide consistent real-time job updates, allowing researchers to identify and respond to failing calculations without having to wait for them to finish.

Bangladesh Inflation Monitor(opens in a new tab)

  • Python
  • FastAPI
  • PostgreSQL
  • Polars
  • Streamlit
  • PaddleOCR
  • Dagster
  • Used Python, FastAPI, and PostgreSQL to build an API and dashboard for monitoring Bangladesh's economic indicators, giving users a single place to view economic data.
  • Built a web scraper and ETL pipeline to collect and transform data from multiple sources, providing a unified and easy-to-understand view of Bangladesh's economy.
  • Used Dagster to schedule and orchestrate the data pipeline and web scraper, automatically updating the dashboard when new monthly economic reports are released and reducing manual maintenance.

Education

University of York logo

York University - Lassonde School of Engineering

B.Sc. Hons. in Computer Science

Toronto, ON, Canada

GPA
3.8 / 4.00
Graduated
2024