Design and maintain AI-serving data pipelines that support production AI workflows
Develop and manage structured data models, transformation logic, and semantic objects used in AI systems
Support ontology development and governance within enterprise platforms for AI use cases
Partner with the Enterprise Data team to ensure AI-serving transformations and semantic models align with foundational data standards and avoid duplication of business logic
Improve data reliability, observability, and performance monitoring practices to support customer-facing and business-critical AI capabilities
Collaborate closely with Applied AI Engineers to enable seamless integration of AI solutions into production environments
Establish reusable data and semantic patterns that enable AI solutions to scale efficiently across multiple use cases
Advance, maintain, and govern AI-serving data and semantic layers that enable reliable, scalable AI solutions.
Requirements
Strong experience in data modeling, relational design, and structured system architecture
Proficient in Python and SQL, including experience designing scalable transformation logic
Experience building and maintaining production-grade data pipelines
Experience working with cloud data platforms (GCP preferred)
Systems-thinking mindset with attention to governance, abstraction, and architectural clarity
Experience supporting ML
or AI-driven systems
Strong communication skills with experience articulating technical concepts to both technical and non-technical stakeholders
Experience with enterprise data platforms
Familiar with infrastructure-as-code or modern DevOps practices
Tech Stack
Cloud
Google Cloud Platform
Python
SQL
Benefits
Quarterly profit-sharing bonus
Hybrid Work schedule
Team member appreciation events and recognition programs
Volunteer opportunities
Casual dress code
On-demand pay options: Access your pay as you earn it, to cover unexpected or even everyday expenses