AI-Driven Data Platform Architect

Position Overview: The Domain Lead for Oracle Cloud Infrastructure is responsible for overseeing a specific technology domain within OCI while integrating business development strategies for Oracle Services and architectural frameworks. This role involves providing strategic direction, managing projects, and ensuring that the domain aligns with overall business objectives, service offerings, and exploring new market opportunities. The Domain Lead will also create technology roadmaps, conduct workshops, and ensure alignment with service offerings to drive organizational success.

We are looking for a skilled AI Data Platform Architect to design and implement data architectures optimized for cloud platforms and AI/ML workloads. The ideal candidate will leverage cutting-edge technologies, cloud infrastructure, and AI-driven approaches to build scalable, secure, and high-performance data ecosystems. You will work closely with cross-functional teams to ensure that data architecture supports cloud-native solutions and AI-driven business intelligence initiatives.

Key Responsibilities:

• Develop and implement domain-specific services strategies and technology roadmaps that align with organizational goals and drive services growth.
• Being recognized as a subject matter expert for your domain
• Plan, design and help customers migrate their on premises workloads to the Oracle Cloud Infrastructure (OCI).
• Experience architecting, building, and maintaining applications on cloud platforms preferably in Oracle cloud
• Lead and manage domain-related projects from inception to completion, ensuring timely delivery, adherence to quality standards, and alignment with architectural principles and service offerings.
• Conduct workshops to facilitate knowledge sharing, gather requirements, and drive collaboration among cross-functional teams and stakeholders.
• Collaborate with IT and business stakeholders to identify needs, opportunities, and market trends that enhance business development efforts to grow the services business.
• Design and maintain scalable architecture solutions that support both current and future business objectives across our services portfolio.
• Mentor and guide team members, fostering a culture of growth and development while ensuring knowledge transfer in architectural practices.
• Stay abreast of industry trends, emerging technologies, and architectural best practices to drive innovation and competitive advantage within the domain.

Specific Skills :

• Cloud Data Architecture Design:
• Develop and maintain cloud-native data architectures, ensuring seamless integration and optimized performance across public, private, and hybrid cloud environments (e.g., AWS, Azure, Google Cloud).
• AI & ML Integration:
• Design data infrastructures that support AI/ML model development, data pipelines, and real-time analytics, enabling advanced machine learning and artificial intelligence capabilities.
• Cloud Data Modeling:
• Design scalable data models for cloud platforms, including data lakes, data warehouses, and real-time streaming architectures. Ensure these models are optimized for AI and big data workloads.
• Cloud Data Integration & ETL Pipelines:
• Architect and manage cloud-based ETL (Extract, Transform, Load) pipelines and real-time data integration solutions to seamlessly ingest, transform, and load large datasets for AI and analytics platforms.
• Data Governance & Security in the Cloud:
• Ensure robust data governance and security protocols are implemented in cloud environments, adhering to data privacy laws, encryption standards, and organizational policies.
• AI-Driven Data Insights:
• Work with data scientists and AI engineers to ensure that the data architecture supports AI-driven decision-making, model training, and real-time predictions at scale.
• Collaboration with Cloud & AI Teams:
• Collaborate closely with AI, data science, and cloud engineering teams to create cloud-based data solutions that deliver on business needs, innovation, and scalability.
• Performance Optimization for Cloud & AI Workloads:
• Continuously monitor, optimize, and troubleshoot data pipelines, storage solutions, and cloud environments to meet the performance needs of data-driven AI applications and business intelligence solutions.
• Cloud Migration Strategy:
• Lead the migration of on-premises data systems to the cloud, ensuring minimal disruption and optimizing cloud storage, compute, and AI capabilities.
• Documentation & Best Practices:
• Develop and maintain documentation for cloud-based data architectures, pipelines, and processes, and ensure adherence to industry best practices in cloud and AI data management.
• AI & Cloud Technology Evaluation:
• Stay up to date with the latest trends in AI, cloud technologies, and data management, and evaluate new tools, platforms, and frameworks for continuous improvement.

Qualifications:

• Bachelor’s degree in Information Technology, Computer Science or a related field.
• Minimum 10 years of enterprise and solution architecture experience (Implementation /Consulting/Operation) required. Hands-on experience is a must.
• Certification in cloud technologies will be an advantage.
• Proven experience in a leadership role within the technology domain with a focus on business development, architecture, services and consumption growth.
• Excellent communication and interpersonal skills, with a track record of successful stakeholder engagement.
• Ability to analyze complex problems, develop effective solutions, and architect scalable systems.

Technical skills

• Proven experience with cloud platforms such as OCI, AWS, Google Cloud, or Microsoft Azure, particularly with data storage, computing, and AI services.
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud-native data processing frameworks.
• Strong experience in designing AI/ML-ready data pipelines and architectures for scalable, real-time analytics.
• Expertise in SQL, cloud data storage (e.g., S3, BigQuery, Azure Data Lake), and cloud-native data warehouses (e.g., Redshift, Snowflake, BigQuery).
• Familiarity with cloud-based AI and machine learning services (e.g., AWS SageMaker, Google AI Platform, Azure ML).
• Experience with cloud data security, encryption, and compliance standards.
• Knowledge of automation and orchestration tools (e.g., Airflow, Kubernetes, Terraform).

Desirable

• Ability to multi-task and work with virtual teams across different engagements.
• Tenacious with a passion for learning new and unfamiliar concepts.
• Flexible to travel when required.
• Relevant local language skills.

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