Kanika Parikh

I am a Data Engineer with over three years of experience, including both an internship and a full-time role. My expertise lies in designing, optimizing, and automating scalable data pipelines using technologies such as Python, SQL, PySpark, Airflow, and Azure. I have a proven track record of collaborating effectively with cross-functional teams to translate business requirements into robust solutions, enhancing efficiency, and achieving significant cost savings through strategic problem-solving.

At Canadian Tire Corporation, I designed and optimized ETL pipelines that integrated multiple data sources into Azure Synapse and Hadoop clusters, boosting pipeline efficiency by 60% and increasing data accuracy to 98%. I also spearheaded a data quality improvement initiative that enhanced quality scores across key loyalty datasets. My experience includes building CI/CD pipelines, migrating legacy ETL processes to cloud-native environments, and proactively addressing data quality incidents, ensuring continuous data integrity.

In my previous role as a Data Analyst Intern at Ontario Power Generation, I automated operational workflows and built dynamic dashboards that significantly improved project tracking and management efficiency. I am passionate about leveraging data to drive insights and support decision-making processes, and I continuously seek opportunities to enhance my skills and contribute to impactful projects.