I am a Master's student in Information Technology at the University of Cincinnati, driven by a deep passion for cloud data engineering, business intelligence, and data-driven solutions. With four years of professional experience, I have a proven track record of developing data ingestion and transformation packages, orchestrating cloud migrations, and building scalable ETL pipelines.In my previous roles, I played a pivotal role in migrating legacy EDW systems to AWS and Snowflake-based Data Lakes, utilizing tools such as DMS, Apache Airflow, and Glue to enable seamless data integration. I have extensive experience in building data pipelines, transforming data using DBT, and replicating complex SSIS methods through custom Python solutions. Additionally, my work includes developing OLAP cubes using SQL Server Analysis Services (SSAS) to empower business stakeholders with multidimensional data analysis capabilities.Key highlights of my experience include developing data ingestion pipelines and ELT models to migrate enterprise data to Snowflake, leading the development of Apache Airflow orchestration models, and creating custom transformations using DBT. I have also implemented and optimized OLAP cubes for advanced data analysis, enhancing both performance and scalability. Furthermore, I ensured robust security, user role management, and conducted extensive performance tuning across systems.In addition to my technical expertise, I am committed to continuous learning and currently pursuing my master’s degree to further hone my expertise in cloud data solutions, AWS technologies, and advanced data analytics. I also hold the AWS Certified Solutions Architect certification.My career goal is to leverage my skills in cloud computing, data engineering, and business intelligence to design scalable, efficient data ecosystems that drive business success. I am eager to collaborate on innovative projects that transform data into actionable insights.Let’s connect to explore opportunities where data meets impactful solutions!