Data Modeler

Intone Inc; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Intone Inc. is seeking an experienced Data Modeler for a 12-month remote contract. You will design, develop, and maintain enterprise data models to support analytics, reporting, data warehousing, and data integration initiatives.

You will collaborate with Data Architects, Data Engineers, analysts, and governance teams to translate complex business requirements into conceptual, logical, and physical data models, including SCDs and domain models.

Qualifications

• 12+ years of experience in data management, data architecture, or related disciplines with hands-on data-modeling
• 7+ years developing conceptual, logical, and physical data models
• Deep understanding of relational and dimensional modeling, normalization, and ER modeling
• Strong knowledge of SQL and relational database concepts

Responsibilities

• Design, develop, and maintain conceptual, logical, and physical data models for enterprise data platforms and analytics solutions
• Translate complex business requirements into scalable data structures
• Develop relational, dimensional models, star/snowflake schemas, and domain-oriented models
• Define entities, attributes, relationships, keys, hierarchies, and reference data structures
• Ensure models support transactional, analytical, historical, and reporting needs
• Collaborate with Data Engineers to fit models into ETL/ELT pipelines
• Maintain documentation and enforce data-modeling standards and definitions

Skills

Enterprise data modeling

Relational & dimensional modeling

SQL proficiency

Data warehousing concepts

Star & snowflake schemas

Requirements translation

Job description

We are seeking an experienced Data Modeler for a 12-month contract position, remote. You will design, develop, and maintain scalable enterprise data models supporting analytics, reporting, operational applications, data warehousing, and data integration initiatives. You will collaborate closely with business stakeholders, Data Architects, Data Engineers, analysts, application teams, and governance teams to translate complex business requirements into well-defined conceptual, logical, and physical data models.

Responsibilities

• Design, develop, and maintain conceptual, logical, and physical data models for enterprise data platforms, analytics solutions, and business applications.
• Translate complex business requirements, business processes, and data requirements into scalable and reusable data structures.
• Develop and maintain relational data models, dimensional data models, star schemas, snowflake schemas, and domain-oriented data models.
• Define entities, attributes, relationships, primary keys, foreign keys, business keys, hierarchies, and reference-data structures.
• Design models that appropriately support transactional, analytical, historical, and reporting requirements.
• Perform model normalization and denormalization based on application, integration, analytics, and performance requirements.
• Design dimensional models for enterprise data warehouses, data marts, and modern analytics platforms.
• Define facts, dimensions, measures, hierarchies, and grain based on business and analytical requirements.
• Design appropriate approaches for maintaining historical information, including Slowly Changing Dimensions (SCDs).
• Ensure models support reporting, BI, advanced analytics, and downstream data-consumption requirements.
• Partner with Data Engineers to ensure models can be effectively implemented within ETL/ELT and data-processing pipelines.
• Define and enforce enterprise data-modeling standards, naming conventions, data types, and modeling best practices.
• Partner with business and technical stakeholders to establish consistent definitions for critical business data.
• Support master data, reference data, metadata management, and data-governance initiatives.
• Identify authoritative data sources and help establish consistent definitions and relationships across enterprise systems.
• Contribute to the development and maintenance of business glossaries and data dictionaries.
• Participate in architecture and model design reviews to ensure proposed solutions comply with enterprise architecture and governance standards.
• Maintain comprehensive documentation for conceptual, logical, and physical data models, including business definitions, data entities and attributes, source-to-target relationships, data lineage, business rules, data ownership, and transformation requirements.
• Maintain model metadata using enterprise modeling and/or data-cataloging platforms.
• Ensure appropriate traceability between business requirements, source systems, data models, transformation logic, and downstream consumption.
• Contribute to data-quality frameworks by identifying mandatory and optional data elements, valid relationships, referential-integrity requirements, data constraints, validation rules, and business rules.
• Work with Data Engineering and Data Governance teams to identify and resolve data-quality and consistency issues.
• Ensure models appropriately support auditability, historical tracking, lineage, and data traceability.
• Identify data redundancies, inconsistencies, and opportunities for standardization and reuse.

Qualifications

• Required
  • 12+ years of experience in data management, data architecture, data warehousing, or related disciplines, with significant hands-on data-modeling experience.
  • 7+ years of strong experience developing conceptual, logical, and physical data models.
  • Deep understanding of relational data modeling, dimensional modeling, star and snowflake schemas, normalization and denormalization, entity-relationship modeling, and data warehousing concepts.
  • Strong understanding of facts, dimensions, hierarchies, grain, surrogate keys, business keys, and Slowly Changing Dimensions.
  • Strong experience defining entities, attributes, relationships, cardinality, primary/foreign keys, and referential-integrity rules.
  • Experience translating complex business requirements into enterprise data structures and models.
  • Strong knowledge of SQL and relational database concepts.