Semantic Data Modeler / Ontologist

Semantic Modeler Job Description Template

This template focuses on the core competencies needed to bridge the gap between complex data and business insights.

Role Summary:

Design and implement enterprise-level semantic layers and dimensional models to enable self-service analytics.

Transform raw data into a coherent, business-ready asset that powers AI/ML accuracy and organizational decision-making.

Key Responsibilities:

Ontology & Taxonomy: Lead the development and governance of business ontologies to ensure consistent data interoperability.

Technical Design: Build and maintain dimensional models (star/snowflake schemas) optimized for high-performance cloud environments like Snowflake or Databricks.

Stakeholder Alignment: Collaborate with business analysts to define clear metrics and conformed dimensions that minimize misinterpretation.

AI Integration: Ground AI systems in business semantics to ensure accurate, trustworthy results for conversational analytics.

Required Qualifications:

Experience: 4 8+ years in data modeling with specific exposure to BI environments and self-service ecosystems.

Technical Skills: Mastery of SQL and proficiency in semantic tools like dbt (MetricFlow), LookML, or Power BI.

Soft Skills: Strong business acumen and the ability to translate complex data sets into clear visual representations for stakeholders.