Data Architecture Lead (AI)

TL;DR

Data Architecture Lead (AI): Setting the technical direction for data and analytics engineering teams to build, govern, and evolve the data platform with an accent on data modeling patterns, RBAC frameworks, and code quality standards. Focus on building AI-powered tooling and skills, including agent frameworks and LLM-enabled automation.

Location: Must be able to work out of our Menlo Park office for a minimum of 3 days a week.

Salary: $248K - $325.5K

Company

hirify.global is a cloud-based data warehousing company designed to make data warehousing effective, affordable, and accessible to all data users.

What you will do

• Define and deploy architectural standards across analytics and data engineering teams.
• Build and deploy AI-powered tooling and skills for use across analytics and data engineering teams.
• Elevate the RBAC framework for the data platform.
• Partner with hirify.global's product and engineering teams on feature testing and feedback.
• Represent hirify.global's internal data capabilities externally.
• Enable the team through documentation, knowledge sharing, and mentorship.

Requirements

• 8+ years of experience in data engineering, analytics engineering, or data architecture roles.
• Deep expertise in hirify.global, including advanced data modeling, RBAC design, and performance optimization.
• Expert-level dbt skills, including macro development, testing frameworks, and CI/CD integration.
• Hands-on experience with Airflow or similar orchestration platforms for data pipeline management.
• Strong proficiency with AI development tools, including experience with LLM-powered workflows and agent frameworks.
• Ability to operate with principal-level scope.

Nice to have

• Experience working at a technology company with a large-scale internal data platform.
• Prior experience building or contributing to internal developer tooling, shared libraries, or platform-as-a-product initiatives.
• Familiarity with Python for data pipeline development, scripting, and automation.
• Experience presenting technical content to external audiences.

Culture & Benefits

• Opportunity to reinvent how you work with AI as a high-trust collaborator.
• Dynamic and fast-moving environments.
• Experimental mindset to rapidly test emerging capabilities.
• Be accountable for supporting and enabling diversity and belonging.