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The GCP Data Engineer will work remotely as part of a full-time team, focusing on utilizing GCP technologies like Big Query and Data Flow to manage and optimize data processes.

The role involves collaborating with data scientists and machine learning engineers to build backend systems and APIs for machine learning models, ensuring optimal infrastructure, and maintaining CI/CD pipelines. Candidates should have strong experience in Java or Python and familiarity with microservices and databases.

The DevOps Architect will be responsible for automating and optimizing the deployment and scaling of AI/ML models, implementing CI/CD automation pipelines in the Azure AI environment, and leveraging cloud-based AI/ML platforms.

The Senior Java Architect will lead the architecture design and manage all phases of application lifecycle, from ideation to execution. Responsibilities include developing solutions to meet both business and non-functional requirements, documentation, and conducting proofs of concept.

The Performance Test Engineer will implement performance testing methodologies and drive best practices across initiatives, focusing on scalable solutions. Key responsibilities include developing performance models, automating testing processes, and mentoring other engineers while ensuring optimal performance across the enterprise environment.

The Senior Database Developer will design, develop, and optimize SQL queries, manage EDI transactions, and integrate data with internal systems. Responsibilities include maintaining database structures, ensuring data integrity, troubleshooting EDI-related issues, and generating reports. Strong skills in SQL programming, EDI standards, and data integration processes are essential.

The Lead Engineer will oversee the administration and optimization of a Kafka cluster, ensuring high performance and stability. Responsibilities include configuration, monitoring, security setup, and troubleshooting of Kafka infrastructure, as well as automating processes and guiding design discussions. Proven leadership and the ability to manage large-scale system implementations are essential.