Data Engineering Lead (AWS + Snowflake)

As a Data Engineering Lead with 9-15 years of experience, you will be responsible for designing, developing, and maintaining scalable data architectures and pipelines for large-scale data platforms. Your expertise in AWS and Snowflake will be crucial in building and optimizing Data Lakes, implementing real-time and batch data processing, and utilizing AWS services for efficient data integration, processing, and analytics. You will collaborate with cross-functional teams to deliver end-to-end data engineering solutions aligned with business goals. Key Responsibilities: - Design, develop, and maintain scalable data architectures and pipelines for large-scale data platforms. - Build and optimize Data Lakes to unify structured and unstructured data sources. - Implement real-time and batch data processing using Snowflake features like Streams, Tasks, and Snowpipe. - Utilize AWS services (EC2, Glue, Lambda, S3, Athena, MWAA) for data integration, processing, and analytics. - Develop and manage PySpark/Python-based workflows for scalable transformations and automation. - Perform data modeling, performance tuning, and optimization in Snowflake. - Collaborate with cross-functional teams to deliver end-to-end data engineering solutions aligned with business goals. Primary Skills: - Strong expertise in AWS and Snowflake - Proficiency in AWS Glue - Hands-on experience with PySpark Additional Skills: - Strong programming skills in Python - Experience with distributed data processing pipelines - Knowledge of Airflow/MWAA for orchestration - Exposure to advanced analytics and secure data sharing,