5 years of experience in data management, data engineering, or data visualization. Experience with Python, AWS, Glue, spark, redshift, Lambda, S3 and strong Sql (DWH). Excellent with AWS side of data engineering. Amazon S3 for storage, AWS Glue for ETL, Amazon Redshift for data warehousing, Amazon Kinesis for real-time data processing, and AWS Lambda for serverless computing. Amazon EMR for large-scale processing and Amazon Athena for querying data, form the core of a data engineering workflow on AWS. Excellent problem-solving, organization, debugging, and analytical skills. Ability to work independently and in a team environment. Excellent communication skills for effectively expressing ideas to team members and clients. Understanding of relational database concepts and SQL querying. Experience with visualization tools - Power BI, will be advantage. Debug and optimize existing data infrastructure and processes as needed. Strong hands-on experience and to lead the team.