AWS Data Engineer

Must Have Skills Strong experience in AWS services (hands-on experience) Data engineering skills (Glue, ECS, Data pipeline etc,) primarily serverless, databases, storage services, container services, schedulers, and batch services. Experience in Snowflake and Data Build Tool. Expertise in DBT, NodeJS and Python. Expertise in Informatica, Power BI, DataStage, Database, Cognos. Knowledge on AI AWS services AI skills – Build AI agents, Gen AI Gitlab CI/CD pipeline Detailed Job Description: Strong experience in AWS services AWS services ( hands-on experience) - Data engineering skills (Glue, ECS, Data pipeline etc.,) primarily serverless, databases, storage services, container services, schedulers, and batch services. Experience in Snowflake and Data Build Tool. Expertise in DBT, NodeJS and Python. Expertise in Informatica, Power BI , DataStage, Database, Cognos. Knowledge on AI AI skills – Build AI agents, Gen AI Gitlab CI/CD pipeline Should have good mix of Data engineering and AI work. Proven experience in leading teams across locations. Knowledge of DevOps processes, Infrastructure as Code and their purpose. Good understanding of data warehouses, their purpose, and implementation. Top 3 responsibilities you would expect the Subcon to shoulder and execute Should have good expertise in delivery coordination Should be able to manage complex software application development and support projects Should be able to manage offshore resources also. Should be able to work with other onsite team members and client Good communication skills.