Senior Manager - Data and AI Architect
Description
Job Description:
Architecture Leadership: Define and maintain the enterprise data and AI architecture, ensuring alignment with business strategy and technology standards.
Solution Design: Architect end-to-end data and AI solutions, including data pipelines, model deployment, and integration with enterprise platforms.
Innovation & Enablement: Evaluate and introduce new technologies, frameworks, and best practices to advance the organization's data and AI capabilities.
Collaboration: Work closely with Data Engineers, AI Engineers, Business Units, and external partners to deliver high-impact solutions.
Platform Optimization: Drive optimization of data storage, processing, and AI model performance across cloud and on-premises environments.
Operating Environment: Enterprise technology landscape with hybrid cloud (Azure), big data platforms, and AI/ML infrastructure.
Framework and Boundaries: Operates within enterprise architecture, data policy, and AI governance frameworks. Adheres to risk, compliance, and budgetary constraints.
Working Relationships: Collaborates with Data & Analytics, Enterprise Architecture, Information Security, Business Units, and external vendors.
Nature of Problems: Designing scalable and secure data/AI architectures, integrating legacy and modern systems, and addressing technical and regulatory challenges.
Approach: Apply structured problem-solving, root cause analysis, and data-driven decision-making. Lead cross-functional teams to resolve architectural and operational challenges.
Required Skills and Experience:
Experience: 10+ years in data architecture, AI/ML solution design, and technology leadership in financial services or technology sectors.
Education: Bachelor's or Master's in Computer Science, Data Engineering, AI/ML, or related field.
Technical Expertise: Deep knowledge of data platforms (e.g., Azure, Databricks), AI/ML frameworks, cloud architectures, data governance, and security.
Skills: Strategic thinking, architecture design, stakeholder management, and effective communication.
Must have: Proven experience architecting and deploying enterprise-scale data and AI solutions.