Senior Data Modeler: Enterprise Data Architect for AI

Teradata; Pierre (SD); On-site; USD 102,000 - 153,000; Full time

Benefits offered by this job

401(k) retirement plan

Health and wellness benefits

Flexible work options

Job summary

Teradata seeks a Senior Data Modeler to lead enterprise data modeling across domains, ensuring scalable, governed data assets for analytics, AI, and knowledge platforms. You will establish modeling standards, align with governance, and collaborate with data engineers and AI teams.

The role requires hands-on expertise in conceptual, logical, and physical modeling, strong SQL, and experience with cloud data platforms, data vaults, and data governance programs.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Management, Mathematics, Engineering, or related field.
• 8+ years of experience in data modeling, information architecture, or enterprise data architecture.
• Demonstrated hands-on expertise creating conceptual, logical, and physical data models for large-scale enterprise environments.
• Deep understanding of relational modeling theory, normalization, dimensional modeling, and analytical schema design.

Responsibilities

• Design and maintain enterprise conceptual, logical, and physical data models across multiple business domains.
• Create scalable data models supporting transactional systems, analytics, and AI workloads.
• Develop canonical data models, business information models, and semantic layers for consistent enterprise understanding.
• Drive standardization of entities, relationships, taxonomies, hierarchies, and business definitions across the organization.

Skills

Data modeling

Enterprise architecture

SQL

Cloud data platforms

Data governance

Stakeholder collaboration

Education

Bachelor's or Master's in CS/IS/Data Management

Tools

Azure

Snowflake

Databricks

Power BI

ER/Studio

Erwin

Job description

Teradata seeks a Senior Data Modeler to lead enterprise data modeling across domains, ensuring scalable, governed data assets for analytics, AI, and knowledge platforms. You will establish modeling standards, align with governance, and collaborate with data engineers and AI teams.

The role requires hands-on expertise in conceptual, logical, and physical modeling, strong SQL, and experience with cloud data platforms, data vaults, and data governance programs.