- Minimum 5 years of professional experience in AWS data integration and management
- 3+ years of hands on development experience in AWS Glue, Lambda functions, CloudFormation, Pyspark
- Hands on working experience in AWS GLUE ETL tool and Strong in Data Engineering concepts
- Must have working experience with SQL, and databases (e.g.: Postgres, Redshift) implementing Data Models.
- Expertise with Python Language and Apache Spark. Have working experience in projects involving these.
- Strong hands on exposure to AWS Analytics services particulary Lambda,Step functions, Glue, Data-Pipelines
- Understanding and technical knowledge on AWS service like EC2, S3. Should have used these technologies in previously executed projects.
- Robust AWS development experience for data ETL/pipeline/integration/automation work. Should have a deep understanding of BI & Analytics Solution development lifecycle.
- Full Flexed in AWS cloud development & Automation for Analytics. Should have a deep understanding of AWS Services (Glue, Lambda, S3, EC2), Visual Studio, SQL Server, SSIS, Matillion; Python
- Strong experience on real-time scalable workflow implementation.