Lead Data Modeler — Enterprise Data Architecture

Apptad Inc; Torrance (CA); On-site; USD 95,000 - 140,000; Full time

Job summary

Apptad Inc in Torrance, CA seeks an experienced Data Modeler to design scalable data models for enterprise platforms, working with business stakeholders, data architects, and engineering teams.

You will translate requirements into conceptual, logical, and physical models, implement star and snowflake schemas, and contribute to data governance and documentation.

Join a collaborative environment focused on data quality, standards, and scalable analytics.

Qualifications

• Hands-on experience with conceptual, logical, and physical data modeling.
• Strong knowledge of relational and dimensional modeling (Star/Snowflake).
• Proficient in SQL, normalization/denormalization, keys and constraints.
• Experience with data warehousing, ETL, and data governance basics.
• Excellent communication and stakeholder management.

Responsibilities

• Collaborate with business and tech stakeholders to capture data needs.
• Develop and maintain conceptual, logical, and physical data models.
• Translate requirements into entities, attributes, and relationships.
• Design normalized and dimensional models for analytics and ops.
• Maintain data dictionaries and modeling documentation.
• Support data integration and governance initiatives.
• Present models and decisions to stakeholders.

Skills

Enterprise data modeling

Conceptual modeling

Logical modeling

Physical modeling

SQL basics

ER modeling

Dimensional modeling

Stakeholder communication

Tools

ERwin

ERStudio

PowerDesigner

Job description

Apptad Inc in Torrance, CA seeks an experienced Data Modeler to design scalable data models for enterprise platforms, working with business stakeholders, data architects, and engineering teams.

You will translate requirements into conceptual, logical, and physical models, implement star and snowflake schemas, and contribute to data governance and documentation.

Join a collaborative environment focused on data quality, standards, and scalable analytics.