- Implemented ETL processes using Informatica for efficient data cleansing, and loading into enterprise data warehouses
- Automated end-to-end data pipelines using Python scripts in Jupyter Notebook, leveraging libraries such as Pandas and TensorFlow to streamline data preprocessing, feature engineering, and predictive analysis
- Integrated Azure Data Factory, Databricks for scalable data transformations, enhancing data reliability and processing speed
- Designed interactive Tableau dashboards and Looker reports, implementing dynamic filters and calculated fields for enhanced data
- Leveraged big data technologies like Hadoop and Hive to process and analyze large datasets, optimizing data workflows
- Managed data integrity and transformation workflows, leveraging CI/CD pipelines and version control