Posted:8 hours ago|
Platform:
Work from Office
Full Time
Develop and maintain data architectures optimized for AI/ML workflows, ensuring data pipelines, storage, and models are scalable and efficient for advanced analytics.
Design and implement data models that support machine learning, AI systems, and data analytics platforms. Integrate data from diverse sources (structured and unstructured) into a unified architecture.
Manage large volumes of data and ensure its availability and quality for AI/ML applications. Leverage technologies like Hadoop, Spark, and cloud platforms (AWS, Azure, Google Cloud) to process and analyse data at scale
Collaborate with data scientists and AI teams to ensure that the data architecture supports the development, training, and deployment of machine learning models. Optimize data flows for model training and performance.
Architect and manage cloud-based data platforms that support AI/ML and analytics workloads. Design solutions for efficient storage, processing, and retrieval of data in cloud environments.
Expertise in AI/ML data architecture, data modeling, and big data technologies (e.g., Hadoop, Spark, Kafka, SQL/NoSQL databases).
Proficiency with cloud platforms (AWS, Azure, Google Cloud) and data storage solutions for AI/ML applications.
Strong understanding of data integration, ETL processes, and real-time data processing.
Knowledge of data governance, privacy, and compliance frameworks in the context of AI and analytics.
Saaki Argus And Averil Consulting
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