AI Data Architect

Overview

The AI Data Architect will lead the architectural direction, standards, and design governance of the AWS-based Data & Analytics platform, with a focus on Redshift and preparing data assets for advanced analytics, AI/ML, and LLM use cases. The role works across platform engineering, data engineering, data modeling, analytics, governance, and business stakeholders as a senior individual contributor.

What you'll do

• 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 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.

What you'll need

• 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 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.

Nice to have

• 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.

Details

• Location: Bengaluru.
• Relocation assistance is provided.