- Design, develop, and maintain data ingestion, transformation, and integration pipelines using Python, PySpark, and SQL.
- Build scalable ETL/ELT workflows for structured and unstructured data across AWS data ecosystems.
- Implement best practices in data quality, performance optimization, and pipeline automation.
- Collaborate with architects and analysts to define data models, schemas, and integration frameworks.
- Work with cloud-native services such as: AWS: Glue, Redshift, S3, Lambda, Pyspark