Data Engineer

Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.

Develop data processing solutions using PySpark and Python for large-scale datasets.

Work with AWS cloud services for data ingestion, processing, storage, and transformation.

Write complex and optimized SQL queries for data extraction, transformation, validation, and reporting.

Build and maintain data pipelines for both batch and incremental data processing.

Perform data cleansing, transformation, validation, reconciliation, and quality checks.

Optimize PySpark jobs and SQL queries for performance and scalability.

Work with AWS data services such as S3, Glue, EMR, Lambda, Redshift or equivalent AWS data platforms.