Develop workflows and ETL data pipelines using Bigdata, Spark, AWS
Build, test, and maintain scalable data pipelines and data architectures that support enterprise analytics use cases
Apply data engineering best practices for performance optimization, reliability, and maintainability and Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Hands-on experience with Bigdata, Spark, AWS and SQL
Knowledge of cloud platforms (AWS) and distributed data processing
Hands-on practical experience in system design, application development, testing, and operational stability
Ability to collaborate effectively within agile teams and across stakeholders
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