Could you briefly share your background and what brought you to this role?

I started my career as a software developer in a small fintech startup where I worked on building data ingestion pipelines using Python and SQL. Over the past two years, I transitioned to a data engineering role at a mid-size e-commerce company, focusing on AWS services such as S3, Glue, and Redshift, and implementing Spark jobs for large-scale data processing. My interest in data pipelines grew from a desire to solve real business problems—like improving recommendation engines and optimizing inventory forecasting—by turning raw data into actionable insights. I enjoy working with cloud-native tools, automating ETL workflows, and ensuring data reliability and performance. This role aligns perfectly with my passion for building scalable, maintainable data infrastructure and my experience with AWS, Python, and Spark.