Lead AWS Data Engineer

📋 Description Design, develop, and maintain scalable data pipelines, ETL/ELT processes. Build cloud-native data solutions using AWS services (Glue, Lambda, Redshift, S3). Develop and optimize large-scale data processing with Python, PySpark, SQL, and PL/SQL. Design and implement enterprise data warehouses, data marts, and dimensional models. Collaborate with stakeholders to deliver data-driven solutions. Ensure data quality, governance, security, and lifecycle management. 🎯 Requirements 8–10 years of experience in Data Engineering, Data Warehousing, and Cloud Data Platform development. Strong AWS expertise: Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3. Advanced proficiency in Python and PySpark for large-scale data processing. Strong SQL and PL/SQL development and optimization. Extensive experience building ETL/ELT pipelines and data ingestion frameworks. Deep understanding of data warehousing concepts and dimensional modeling.