Parvish Gajjar
Data Engineer i @TD
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WORK HISTORY
Data Engineer i @TD
Toronto, ON, CA
Developed and optimized ETL pipelines in Azure Cloud using Databricks, Data Factory, and Synapse for efficient data processing- Enhanced performance of a 5B+ record data asset by 97% through optimized SCD2 island pattern implementation in ETL workflows- Proactively conducted Data Quality Investigations to ensure data integrity and prevent issues- Preparing to contribute to AI Engineering initiatives as part of upcoming role responsibilities.
EDUCATION
Gujarat Technological University (GTU)
Bachelor of Engineering, Information Technology
Dalhousie University
Master of Applied Computer Science, Computer Science
Seventh Day Adventist Higher Secondary School
High School, Science
ABOUT PARVISH GAJJAR
My journey in technology started with a simple passion and has evolved into a career focused on delivering high-impact, scalable solutions. As a Data Engineer I at TD, I specialize in the Azure Cloud stack, mastering tools like Databricks, Azure Synapse, and Data Factory. I pride myself on building efficient systems. My most significant recent achievement was enhancing the performance of a 5B+ record data asset by 97% through optimized SCD2 implementation, directly improving data processing efficiency.With a Master\'s in Applied Computer Science (Dalhousie University), I bring a strong foundation in both software architecture and data science. Earlier in my career, I developed and maintained a backend algorithm for a product used by a state government in India for predicting traffic, achieving a validated 91% accuracy. I thrive in agile, collaborative environments and continuously seek out opportunities to innovate, whether by automating monitoring with GitHub workflows or proactively conducting Data Quality Investigations. I\'m excited to leverage my expertise as I prepare to contribute to AI Engineering initiatives.My Toolkit Includes:Cloud: Azure (Primary), AWS, GCP.Big Data: Azure Synapse SQL, Azure Data Lake, Azure Data Factory, Databricks.Core Languages: Python, Node.js, JAVA.
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