About This Role
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,
enabling 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, enabling 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.
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