Toronto, Ontario, Canada
As a Data Engineer, I specialize in building real-time, large scale data pipelines and high throughput systems that power data driven decisions. Leveraging Python, SQL, PySpark, and Big Data technologies like Spark, Kafka, and Hadoop, I create scalable solutions that turn complex datasets into actionable insights. πππ² πππ«ππ§π ππ‘π¬: βͺοΈ Real-Time Data Pipeline Design β Building resilient pipelines for ingestion, transformation, enrichment, and delivery. βͺοΈ Scalable Infrastructure β Designing systems using AWS, PostgreSQL, Redis, and document stores like Cassandra. βͺοΈ Performance Optimization β Improving data flow reliability, latency, and throughput. βͺοΈ Data Modeling β Structuring conceptual and physical models for warehousing and analytics. βͺοΈ Cloud & Data Lakes β Managing data lakes and workflows using AWS, Airflow, and S3-based architectures. βͺοΈ Data Visualization & BI β Translating complex data into clear, compelling visuals using Power BI, Tableau, and Looker to support business teams and drive strategic decisions. βͺοΈ KPI & Dashboard Development β Creating automated, dynamic dashboards and performance tracking systems aligned with key business objectives. Iβm passionate about using modern tools like Unix, Bash, Git, and CI/CD pipelines, to streamline processes and make a meaningful impact through data. I enjoy working cross-functionally with analysts, engineers, and business teams to translate insights into real-world results. Letβs connect if youβre interested in collaboration, insights, or just exchanging ideas. π© [email protected]
β’ Designed and implemented an end-to-end data ingestion pipeline to scrape video/audio files and metadata from web sources, automating content extraction using Python and Playwright. β’ Structured and validated metadata against a defined schema and loaded it into BigQuery for scalable querying and downstream analytics. β’ Integrated Google Cloud Storage to store raw media assets and ensured seamless pipeline execution from data scraping to cloud storage using GCP-native tools. β’ Collaborated with team members to ensure data availability and quality. β’ Optimized data workflows and performed data integration tasks. β’ Worked with large datasets and developed solutions for data storage and access. β’ Ensured data security and adherence to best practices.
β’ Designed and implemented enterprise-level data solutions using Azure Data Lake, Azure Synapse Analytics, and Microsoft Fabric, improving data accessibility and reducing processing times by 20%. These solutions supported seamless integration for real-time analytics, enhancing overall data management and availability. β’ Developed and optimized ETL pipelines using Azure Data Factory and Databricks to extract, transform, and load high-complexity datasets from multiple sources. Streamlined data integration processes, reducing manual data handling by 40% and improving reporting accuracy across the business. β’ Collaborated with financial market teams and front office stakeholders to build financial models, utilizing Power BI and SQL Server for in-depth data analysis and dashboard creation. These insights directly supported decision-making for senior leadership, enhancing financial planning and forecasting capabilities. β’ Created strategic dashboards and real-time reports for key stakeholders including executives, financial leaders, and project managers, leveraging Power BI and Azure Analysis Services. These reports improved operational efficiency by 15%, driving critical business insights and supporting data-driven decision-making. β’ Led the development and automation of data pipelines using Azure Data Factory, Azure Functions, and Databricks, dedicating 50% of my time to designing scalable cloud-based solutions. This improved data flow and reduced processing costs by 20%, while optimizing data pipelines for real-time analytics. β’ Championed CI/CD pipeline implementation with Azure DevOps, incorporating automated testing and version control practices. Ensured high-quality data engineering standards across all cloud-based solutions, reducing deployment times by 50% and ensuring consistency in updates.
β’ Designed and optimized enterprise applications by integrating data solutions, automating workflows, and implementing SQL, Python, and BI tools, improving application performance and decision-making for PMI. β’ Led requirement gathering sessions with stakeholders to ensure alignment and effective communication on project goals. β’ Developed and optimized SQL queries, stored procedures, and triggers in Azure SQL and SQL Server, increasing data processing efficiency by 30%. β’ Led the development and deployment of end-to-end BI solutions integrating Power BI and SQL, resulting in improved data visualization and better decision-making. β’ Managed and documented project scope, schedule, and risks for 10+ web-based projects, contributing to on-time delivery. β’ Created workflow diagrams, process maps, and SOPs for seamless integration of eCommerce tools within financial applications. β’ Participated in Agile and Waterfall methodologies for web application development, ensuring efficient feature deployment and iterative improvements. β’ Supported change management and post-implementation activities to ensure operational readiness and smooth business transitions.