Data Engineering

You will lead data engagements on GCP focusing on data lakes, migration, and warehouse solutions. Responsibilities Lead multiple data engagements on GCP Cloud covering data lakes, engineering, and business intelligence. Design and develop distributed, high-volume multi-thread batch, real-time, and event processing systems. Interface with IT and business stakeholders to translate requirements into functional and non-functional specifications. Implement systems to validate data and monitor quality to ensure accuracy and availability. Mentor junior talent and contribute to the development of internal assets and accelerators. Required Skills 15+ years of experience in technical, solutioning, and analytical roles. 5+ years of experience building and managing Data Lakes, Data Warehouses, and Data Integration solutions in GCP, AWS, or Azure. Expertise in Spark, PySpark, and Scala. Hands-on experience with Dataflow and DynamoDB. Proficiency with Oracle and other Cloud/On-Premise databases. Experience architecting end-to-end data pipelines for structured and unstructured data. Deep understanding of distributed computing environments like Hadoop and Cloud platforms. Ability to define non-functional boundaries including scalability, performance, security, and resilience. Experience managing business transformation projects for migrating on-premise data to the cloud. Preferred Skills Experience with Machine Learning frameworks such as TensorFlow or PyTorch. You will lead data engagements on GCP focusing on data lakes, migration, and warehouse solutions. Responsibilities Lead multiple data engagements on GCP Cloud covering data lakes, engineering, and business intelligence. Design and develop distributed, high-volume multi-thread batch, real-time, and event processing systems. Interface with IT and business stakeholders to translate requirements into functional and non-functional specifications. Implement systems to validate data and monitor quality to ensure accuracy and availability. Mentor junior talent and contribute to the development of internal assets and accelerators. Required Skills 15+ years of experience in technical, solutioning, and analytical roles. 5+ years of experience building and managing Data Lakes, Data Warehouses, and Data Integration solutions in GCP, AWS, or Azure. Expertise in Spark, PySpark, and Scala. Hands-on experience with Dataflow and DynamoDB. Proficiency with Oracle and other Cloud/On-Premise databases. Experience architecting end-to-end data pipelines for structured and unstructured data. Deep understanding of distributed computing environments like Hadoop and Cloud platforms. Ability to define non-functional boundaries including scalability, performance, security, and resilience. Experience managing business transformation projects for migrating on-premise data to the cloud. Preferred Skills Experience with Machine Learning frameworks such as TensorFlow or PyTorch.