Senior Data Modeler
KPI Partners
About KPI Partners
KPI Partners. A global leader in Analytics and Digital Transformation, helping the world's most data-driven organizations turn raw data into competitive advantage. We build composable Customer 360 platforms, modern data architectures, and AI-powered analytics solutions across retail, B2B, industrial, and enterprise clients. Our people are practitioners first — we deliver, we don't just advise.
Title: Senior Data Modeler
Job type: Contract – 3 Months
Location: San Diego, CA (Hybrid)
Key Skills: Data Modeling, Databricks, and Unity Catalog.
Nice to Have: Exposure to the Finance Domain.
About the Role:
We are looking for an experienced Data Modeler to design, develop, and maintain scalable enterprise data models that support analytics, reporting, operational applications, and data integration initiatives. The Data Modeler will work closely with business stakeholders, data architects, data engineers, analysts, and application teams to translate business requirements into clear conceptual, logical, and physical data models. The role will help establish consistent data definitions, relationships, standards, and governance practices across the organization.
The ideal candidate will have strong experience in enterprise data modeling, relational and dimensional modeling, data warehousing, cloud data platforms, and modern data architecture practices. Experience supporting finance data domains and harmonized enterprise data models is preferred. Experience in the Financial domain would be a great plus.
Key Responsibilities:
- Design and maintain conceptual, logical, and physical data models for enterprise data platforms and business applications.
- Translate business requirements and processes into scalable, reusable data structures.
- Develop relational, dimensional, star-schema, snowflake-schema, and domain-oriented data models as appropriate.
- Define entities, attributes, relationships, primary keys, foreign keys, business keys, hierarchies, and reference-data structures.
- Define and enforce naming conventions, modeling standards, data types, and modeling best practices.
- Partner with business and technical teams to establish consistent definitions for critical business data.
- Support master data, reference data, metadata, and data-governance initiatives.
- Maintain model documentation, business definitions, lineage, and metadata in enterprise modeling or cataloging tools.
- Participate in design reviews and ensure proposed database and analytics
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