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Experience

Where I've worked

  1. TD logo

    Data Engineer @ TD

    Sep 2026 – Dec 2026
    • Engineered and maintained Azure ETL pipelines processing 2,500-3,000 documents per ingestion cycle across Databricks, Azure SQL, and Data Lake.
    • Optimized AI data pipelines and embedding infrastructure, improving retrieval accuracy from 95% to 98% while reducing provisioned compute by 47%.
    • Built cloud infrastructure, CI/CD, and Datadog monitoring across DEV/TEST/PROD, enabling more reliable deployments and faster incident triage.
    AzureAzure DatabricksAzure SQLAzure Data Lake StorageCI/CDDatadog
  2. CIBC logo

    Data Engineer @ CIBC

    May 2026 – Aug 2026
    • Resolved 100+ production incidents via root-cause analysis, maintaining 98%+ uptime across 4+ systems spanning Azure, Databricks, and SQL.
    • Managed and improved Databricks queries and Azure Data Factory pipeline reliability to strengthen workflow stability in production.
    • Supported deployments and release management through Azure DevOps and Salesforce, improving production workflows and deployment reliability.
    AzureAzure DatabricksAzure Data FactoryAzure DevOpsSalesforceSQL

  3. AI Software Developer Intern @ Varonova Tech Inc.

    Jan 2026 – Apr 2026
    • Refactored an AI video generation pipeline into modular object-oriented Python architecture, separating scene proxy operations, depth processing, and rendering for maintainability and consistent workflows.
    • Implemented a 3D point cloud reconstruction pipeline using NumPy, with depth backprojection, 4x4 camera pose transformations, and voxel-based downsampling to generate optimized scene proxies.
    • Developed a novel-view rendering pipeline with z-buffer occlusion, point splatting, OpenCV inpainting, and FFmpeg H.264 export for downstream AI video generation workflows.
    PythonNumPyOpenCVFFmpeg3D RenderingPoint Clouds
  4. Western Cyber Society logo

    Software Developer @ Western Cyber Society

    Sep 2025 – May 2026
    • Designed and developed LedIq, a functional replica of a top-5 banking system on IBM z/OS using COBOL, JCL, SQL, and REXX, integrated with a Node.js frontend and FastAPI backend for low-latency risk evaluation.
    • Deployed an ONNX-hosted XGBoost model for real-time risk scoring and added SHAP explainability, persisting predictions and feature-level explanations in IBM Db2 for auditability.
    IBM z/OSCOBOLJCLNode.jsFastAPIXGBoostSHAPDb2

  5. Software Engineer @ CognitomeAI

    Sep 2025 – Dec 2025
    • Built a Python/FastAPI pipeline to ingest, clean, index, and retrieve PhD and peer-reviewed papers using NLP, embeddings, vector search, and semantic similarity.
    • Developed an interactive data visualization that clusters and ranks papers by relevance using statistical analysis and similarity scoring to support faster data-driven decisions.
    • Built and deployed a GPT-3.5 RAG chatbot using Python, Docker, AWS, and Next.js for citation-backed research workflows.
    PythonFastAPINLPEmbeddingsVector SearchGPT-3.5DockerAWSNext.js
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