AI Data Architect

Job Description Summary

Job Description

Key Responsibilities

• Provide architectural leadership for the Data & Analytics platform, including target-state direction, principles, standards, and guardrails
• Guide the evolution of the AWS-based analytics environment, with particular focus on Redshift architecture, scalability, reliability, maintainability, and performance
• Define and maintain best practices across ingestion, orchestration, data modeling, BI consumption, platform usage, and AI data readiness
• Review, challenge, and validate solution designs proposed by development teams to ensure alignment with platform standards and enterprise architectural principles
• Support governance and quality improvement through practical architecture review, design oversight, and standards adoption
• Help shape platform capabilities that improve data readiness for AI/ML and LLM-related use cases, including metadata quality, discoverability, governed reuse, lineage visibility, and fit-for-purpose data preparation
• Provide guidance on modern data architecture patterns relevant to AI enablement, including lakehouse architecture, feature stores, vector database concepts, and related design considerations where appropriate
• Promote effective use of metadata, cataloging, and governance capabilities to improve data discovery, trust, interoperability, and cross-platform connectivity
• Collaborate with platform, engineering, analytics, governance, and business stakeholders to align technical direction with enterprise priorities and delivery needs
• Facilitate cross-team design discussions, technical decision-making, and trade-off analysis across multiple teams and stakeholders
• Measures of Success
• Improved architectural consistency across teams and platform domains
• Higher quality, more scalable, and more maintainable solution designs
• Stronger adoption of platform standards, guardrails, and best practices
• Improved coordination between platform, development, and data modeling teams
• Stronger governance and better technical decision quality across the platform
• Improved reliability, maintainability, and long-term sustainability of the environment
• Better metadata quality, discoverability, lineage visibility, and governance to support analytics and AI-ready data usage
• Improved readiness of data assets and platform capabilities for AI/ML and LLM-related use cases
• Effective support of strategic initiatives that require cross-team architectural leadership and coordination

Required Qualifications

• 6–8 years of experience in a similar AI data architecture, platform architecture, data architecture, solution architecture, platform engineering, or senior data engineering role within a cloud-based Data & Analytics environment
• Strong experience with AWS services and architectural principles relevant to enterprise data and analytics platforms
• Strong understanding of Redshift-based analytical data environments
• Experience across key Data & Analytics capabilities, including ingestion, orchestration, data modeling, analytics consumption, and platform operations
• Demonstrated ability to define standards, architectural patterns, and design guardrails across multiple teams
• Proven experience reviewing, challenging, and validating technical solutions proposed by engineering and data teams
• Practical working knowledge of SQL and analytics tools sufficient to assess technical designs and engage credibly with delivery teams
• Familiarity with modern data architecture patterns that support AI/ML use cases, including lakehouse architecture, feature stores, and vector database concepts
• Practical understanding of data preparation, metadata, governance, and discoverability needs that support downstream AI, ML, and LLM use cases
• Preferred Qualifications
• Experience with HVR and/or Fivetran in enterprise ingestion environments
• Familiarity with Tableau and Power BI in governed analytics ecosystems
• Experience with data fabric, data mesh, or other distributed data architecture models, including decentralized ownership and federated governance
• Experience with modern metadata, catalog, lineage, or governance platforms that improve discovery and interoperability
• Experience improving metadata management, cataloging, governance processes, or platform transparency
• Experience with enterprise architecture practices, platform modernization, or operating model improvement
• Exposure to AI/ML platform enablement patterns, including governed data provisioning for LLM use cases
• Certifications in AWS, architecture, data engineering, or project/program management
• Experience participating in architecture review boards, design authorities, or technical governance forums

Additional Information

Preferred Qualifications

• Experience with HVR and/or Fivetran in enterprise ingestion environments
• Familiarity with Tableau and Power BI in governed analytics ecosystems
• Experience with data fabric, data mesh, or other distributed data architecture models, including decentralized ownership and federated governance
• Experience with modern metadata, catalog, lineage, or governance platforms that improve discovery and interoperability
• Experience improving metadata management, cataloging, governance processes, or platform transparency
• Experience with enterprise architecture practices, platform modernization, or operating model improvement
• Exposure to AI/ML platform enablement patterns, including governed data provisioning for LLM use cases
• Certifications in AWS, architecture, data engineering, or project/program management
• Experience participating in architecture review boards, design authorities, or technical governance forums
• Additional Information
• Relocation Assistance Provided: Yes