Key skills
AWSCloudAIGenerative AIGenAIRAGAgenticData EngineeringData WarehousingAnalyticsSnowflakeECSEKSLambdaS3GlueBedrockPerformance OptimizationLeadershipStakeholder ManagementCommunication
About this role
Role Overview
- Lead the architecture and design of enterprise Data & AI platforms supporting analytics, reporting, and AI-driven business capabilities.
- Partner with business and technology stakeholders to identify and prioritize high-value AI and data modernization opportunities.
- Define scalable data architecture, governance, security, and compliance frameworks aligned with banking and regulatory requirements.
- Architect and guide implementation of AI, Generative AI, and Agentic AI solutions leveraging enterprise data assets.
- Provide technical leadership across data engineering, AI engineering, and platform teams.
- Establish architecture standards, best practices, and future-state roadmaps for data and AI capabilities.
Requirements
- 12-15 years of experience in Data Architecture, Data Engineering, AI Data Platforms, and AI/GenAI solutions, with proven experience designing and delivering large scale projects
- Strong Banking and Financial Services domain experience with understanding of lending, commercial banking, risk, finance, regulatory reporting, customer data, and enterprise data management.
- Proven experience designing and implementing enterprise-scale data platforms in highly regulated environments with a strong focus on governance, security, compliance, and auditability.
- Deep expertise in data architecture, data engineering, data warehousing, data lakes, lakehouse architectures, data modeling, metadata management, and data governance.
- Hands-on experience designing end-to-end data platforms, including ingestion, integration, transformation, storage, data quality, lineage, and consumption layers.
- Strong expertise with Snowflake, including Snowpark, Cortex, Cortex Analyst, Cortex Search, Iceberg integration, data sharing, security, and performance optimization.
- Strong experience with AWS services including S3, Glue, Lambda, EMR, ECS/EKS, and related cloud-native data engineering services.
- Experience architecting modern cloud-based data platforms leveraging Snowflake and AWS.
- Strong understanding of Generative AI, LLMs, RAG, Vector Databases, AI Agents, Multi-Agent Architectures, and Agentic AI patterns.
- Hands-on experience designing and deploying AI solutions using Snowflake Cortex, AWS Bedrock, and enterprise AI frameworks.
- Experience integrating AI capabilities into enterprise data platforms while ensuring governance, security, and responsible AI practices.
- Excellent stakeholder management, communication, and leadership skills with the ability to bridge business and technology teams.
Tech Stack
- AWS
- Cloud