As a Data Engineer at Scotiabank, I build and optimize Big Data ETL pipelines to provide a unified analytics platform for batch and streaming data. I use technologies such as GCP, Azure, Spark, Python, Databricks, Kubernetes, Airflow, and IoT to deliver scalable and reliable solutions that enable data-driven decisions for the organization. With a Master of Management Analytics (MMA) from Queen's University, I have the skills and knowledge to apply advanced analytics and machine learning techniques to solve real-world business problems. I also have a background in Business Analysis and Artificial Intelligence from the University of Toronto, where I learned SQL, Tableau, Power BI, and Machine Learning Algorithms. I am passionate about data science and visualization, and I have multiple certifications in these domains from LinkedIn and Tableau. I aim to leverage my expertise and experience to create value and impact through data. I enjoy collaborating with cross-functional teams and stakeholders to deliver innovative and effective solutions. Key Competencies: ~ Designing & Creating Big Data ETL Pipelines ~ Pipeline Automation ~ Building a Unified Analytics Platform ~ Optimize the Job Execution Time Technologies: GCP, Microsoft Azure, Spark, Python, Databricks, Kubernetes, Airflow, Spark Streaming, IoT, HDFS, SQOOP, Hive, Bitbucket, Jenkins, Agile, Confluence.