Role: Semantic Modeler / AI Engineer
Location: Seattle, WA/Dallas, TX
Duration: 6 months (can extend)
Must-Have Technical / Functional Skills
We are looking for a talented AI Data Engineer and Semantic Modeler to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining metric stores and semantic models to support AI and machine learning initiatives. A strong foundation in data architecture, data modeling, and AI technologies is essential.
Technical Skills:
Proficiency with AI-related technologies such as dbt MetricFlow, Neo4j knowledge graphs, AtScale, AWS QuickSight, and AWS Neptune
Advanced expertise in SQL and data modeling, with experience in relational databases such as Amazon Redshift, RDS, and Databricks
Roles and Responsibilities
Define data models tailored to specific business requirements
Standardize metrics and KPIs across the organization
Implement and manage metric store tools, including dbt MetricFlow and the dbt Semantic Layer
Map semantic models to the underlying data layer
Design, develop, and refine models based on evolving business needs
Apply generative AI use cases where applicable to drive business value
Maintain MLOps practices to automate and monitor machine learning pipelines
Stay current with emerging trends in AI, data engineering, and semantic technologies
Leverage hands-on experience with AI technologies such as dbt MetricFlow, Neo4j knowledge graphs, AtScale, AWS QuickSight, and AWS Neptune
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