Data AI Architect

Role Overview:

This role is for a Data AI Architect tasked with leading modern data architecture and AI-enabled implementations across the data portfolio. The architect will design and operationalize a Lakehouse ecosystem, enable Data-as-a-Service through reusable data products and APIs, and support real-time learning patterns for analytics and GenAI use cases. This position requires partnering closely with executive stakeholders to solve high-impact, real-time business problems with a balanced strategic and pragmatic mindset.

Key Responsibilities:

• Lead modern data architecture and AI-enabled implementation across the data portfolio.
• Design and operationalize a Lakehouse ecosystem, including Bronze, Silver, and Gold layers.
• Enable Data-as-a-Service through reusable data products and APIs.
• Support real-time learning patterns for analytics and GenAI use cases.
• Partner with executive stakeholders to solve high-impact, real-time business problems.
• Build and guide scalable data pipelines, data models, and integration patterns across heterogeneous sources and platforms.
• Implement AI/GenAI solutions within enterprise contexts.
• Embed data governance into architecture using tools and processes such as Collibra, Alation, and Informatica.

Required Skills:

• Strong hands-on expertise with modern data platforms and architectures, including ETL/ELT, streaming, and event-driven patterns.
• Proven ability to build and guide scalable data pipelines, data models, and integration patterns.
• Experience implementing AI/GenAI solutions in enterprise contexts.
• Solid engineering fundamentals and a production readiness mindset.
• Working knowledge of data governance and cataloging tools/processes (e.g., Collibra, Alation, Informatica).
• Data Architecture and Modeling.
• Enterprise Architecture.

Qualifications:

• 10+ years of experience.

Preferred Skills:

• Strong Google Cloud exposure and integration with data services (e.g., BigQuery, Cloud Storage) and scalable runtime options.