Requirements
Education: Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.Experience:15+ years of experience in data architecture, data engineering, or AI/ML roles.Proven experience in designing and implementing data models and architecture in large-scale data environments.Experience with AI and machine learning frameworks, libraries, and tools.Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark).Skills:Strong knowledge of database systems (SQL and NoSQL) and data warehousing concepts.Excellent analytical and problem-solving abilities.Strong communication skills, with the ability to convey complex data concepts to non-technical stakeholders.Ability to work collaboratively in a team-oriented environment.
Description
Eram Talent, a leading talent acquisition company, is on the lookout for a highly skilled Data & AI Architect to join our team in Saudi Arabia. The Data & AI Architect will be instrumental in designing and implementing data-driven solutions that leverage advanced analytics and artificial intelligence to empower business decisions across various projects in the region.This role requires a deep understanding of data architecture, data modeling, and AI/ML technologies. The architect will collaborate with cross-functional teams to ensure that the data architecture is robust, scalable, and aligned with the business strategies. This position offers an exciting opportunity to innovate and shape the future of data utilization within organizations.ResponsibilitiesOwn enterprise data architecture and extend it to AI and MLOps capabilities to enable trusted analytics and scalable AI delivery.Develop and implement a comprehensive data architecture strategy that supports business goals and AI initiatives.Design data models, database structures, and data flow processes to ensure data integrity, availability, and security.Design and oversee the implementation of advanced analytics solutions, including machine learning models and algorithms.Collaborate with data engineering and data science teams to ensure that data pipelines are efficient and aligned with AI/ML requirements.Establish best practices for data governance, data quality, and data lifecycle management.Support the selection and implementation of data management tools and technologies.Engage with stakeholders to understand their data needs and ensure that data solutions deliver maximum business value.Monitor trends in the data and AI landscape, refining strategies as necessary to drive continuous improvement and innovation.