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This role is focused on designing and building enterprise Data & AI platforms across hybrid environments, integrating on-premise platforms with modern cloud services. Key responsibilities include defining enterprise architecture for data platforms to enable scalable analytics and real-time data processing within the banking sector, architecting and implementing event streaming platforms using Confluent Kafka, and building Digital Data Store platforms on Azure Cosmos DB. Additional tasks involve designing enterprise AI architectures, implementing MLOps solutions, and representing the Data & AI Architecture domain in governance councils.
Key Responsibilities:
- Design and build enterprise Data & AI platforms across hybrid environments, integrating on-premise platforms (e.g., Cloudera) with modern cloud services (e.g., Azure).
- Define enterprise architecture for data platforms, streaming systems, and AI workloads to enable scalable analytics and real-time data processing across banking domains.
- Architect and implement enterprise event streaming platforms using Confluent Kafka for real-time integration across core banking, digital channels, and enterprise applications.
- Design Digital Data Store (DaaS) platforms (e.g., on Azure Cosmos DB) to serve enterprise data domains such as Customer, Accounts, Loans, Cards, Wealth, and Transactions.
- Build domain-based data products and data marts supporting Customer 360, Wealth 360, and enterprise analytics use cases.
- Design and implement enterprise AI and GenAI platform architectures using cloud-native AI services (e.g., Azure OpenAI Service, Azure AI Foundry) for secure and governed AI workloads.
- Define enterprise AI reference architectures, including LLM integration, RAG patterns, vector search pipelines, and secure API-based AI services.
- Design MLOps architecture using Databricks MLflow and Azure ML for model lifecycle management, experiment tracking, and scalable AI deployment.
- Implement GenAI solutions, such as NLP-to-SQL data assistants and internal AI chatbots for natural language interaction with enterprise data platforms.
- Represent the Data & AI Architecture domain in enterprise architecture forums and AI governance councils, contributing to AI standards and technology strategy.
Technical Skills & Tech Stack:
- Data Platforms & Architecture: Data Lakes, Lakehouse, Real-time Streaming Platforms, Data Warehouse, NoSQL, Data Modelling, Data Governance.
- Big Data & Streaming: Cloudera (CDP), Confluent Kafka, Databricks.
- Cloud Infrastructure (Azure prioritized): Azure ADLS, Azure Data Factory, Azure Synapse, Azure Databricks, CosmosDB (Mongo vCore), Azure DevOps.
- AI/ML & GenAI: Azure OpenAI, Azure AI Foundry, MLflow, Azure ML, LLM integration, RAG patterns.
Language Requirements: Not specified.
Work Conditions: Hybrid, Full-time
Location: Dubai, Dubai, United Arab Emirates
