We are seeking an experienced AI & Data Specialist to lead the design, implementation, and optimization of enterprise-scale data and artificial intelligence solutions within a cloud-first environment. This role is ideal for professionals with strong expertise in data architecture, data engineering, AI/ML deployment, and Oracle Cloud technologies who are passionate about transforming data into business value.
Detailed Job DescriptionAs an AI & Data Specialist, you will play a critical role in building scalable, secure, and intelligent data platforms that support advanced analytics and AI-driven decision-making. You will be responsible for designing modern data architectures, developing robust data pipelines, and deploying machine learning solutions in cloud environments. Working closely with business stakeholders, architects, data scientists, and engineering teams, you will ensure the successful delivery of enterprise-grade data solutions that meet performance, scalability, and governance requirements. The ideal candidate will have hands-on experience with Oracle Cloud Infrastructure (OCI), Oracle AI Services, or equivalent cloud AI ecosystems, coupled with a strong understanding of data engineering and cloud-native architectures.
Key Responsibilities Design and implement enterprise-scale data architectures and cloud-based data platforms. Develop, optimize, and maintain scalable data pipelines and data integration frameworks. Deploy, manage, and monitor AI and machine learning models within production environments. Utilize cloud-native services to support advanced analytics, AI, and business intelligence initiatives. Design data solutions that ensure scalability, security, reliability, and high performance. Collaborate with data scientists, engineers, and business stakeholders to translate requirements into technical solutions. Implement data governance, quality, and compliance frameworks across data ecosystems. Integrate AI services, analytics platforms, and business applications through APIs and cloud services. Support advanced analytics, reporting, and predictive modeling initiatives. Monitor platform performance and recommend continuous improvements to data and AI infrastructure. Create technical documentation, architecture diagrams, and implementation standards. Stay current with emerging AI, cloud computing, and data engineering technologies. Required Qualifications & Skills Bachelor's Degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. Strong experience in Data Architecture and Data Engineering. Hands-on experience deploying and managing AI and Machine Learning solutions. Proven experience with cloud-native data and AI platforms. Strong understanding of data pipelines, ETL/ELT frameworks, and large-scale data processing. Experience designing scalable enterprise data solutions and modern data architectures. Strong knowledge of analytics platforms, data warehousing, and cloud data ecosystems. Experience working within enterprise-scale cloud environments. Strong analytical, problem-solving, and troubleshooting skills. Excellent communication and stakeholder-management capabilities. Ability to work effectively in cross-functional and multicultural environments. Nice-to-Have Skills Strong Oracle Cloud Infrastructure (OCI) experience. Hands-on experience with OCI Data Science services. Experience with Oracle AI Services and Oracle's Data & AI ecosystem. Knowledge of cloud-based machine learning operations (MLOps). Experience with data lakes, data warehouses, and real-time analytics platforms. Multi-cloud experience across AWS, Microsoft Azure, or Google Cloud Platform. Relevant cloud, AI, or data engineering certifications. Recruitment Pro TipFor AI and Data Specialist roles, employers are particularly interested in real-world implementations rather than theoretical knowledge. Highlight specific projects where you designed data architectures, built data pipelines, deployed AI/ML models, optimised cloud platforms, or delivered measurable business outcomes such as reduced processing times, increased data quality, improved forecasting accuracy, or enhanced operational efficiency. Quantifiable achievements can significantly strengthen your application. #J-18808-Ljbffr
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