> Markdown version of [/jobs/ext/4692028-data-modeler](https://www.wearedevelopers.com/jobs/ext/4692028-data-modeler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Modeler - **Company:** Infodyne Solutions - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Data Architecture, Data Dictionary, Information Engineering, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Mapping, Data Migration, Data Structures, Data Warehousing, IBM DB2, Relational Databases, Database Design, Database Development, Dimensional Modeling, Information Lifecycle Management, PostgreSQL, Metadata, Microsoft SQL Server, MySQL, Oracle (Applications), Standard Sql, Teradata SQL, Enterprise Data Management, Indexer, Information Technology, Data Lineage, Data Management - **Published:** November 12, 2026 - **Apply:** https://www.dice.com/job-detail/ff0275b0-7553-42ac-aaf4-244691a364fe ## About the Role * Bachelor's or master's degree in computer science, Information Technology, Data Management, Engineering, or a related field. * 8+ years of experience in data modeling, database design, data architecture, or a similar role. * Strong understanding of conceptual, logical, and physical data modeling concepts. * Proven experience with relational database design, normalization, denormalization, indexing, keys, constraints, and referential integrity. * Experience designing data warehouse and analytical models. * Strong knowledge of SQL and database development. * Experience with one or more relational database platforms: * Oracle * Microsoft SQL Server * PostgreSQL * MySQL * Teradata * IBM Db2 Experience with dimensional modeling concepts, including facts, dimensions, slowly changing dimensions, measures, and hierarchies. Experience working with data integration, ETL/ELT, data migration, and source-to-target mapping. Strong understanding of data architecture principles, data lifecycle management, and enterprise data management. Experience creating data dictionaries, metadata documentation, data lineage, and business glossaries. Ability to interpret complex business requirements and convert them into effective data structures. Experience collaborating with business stakeholders, technical teams, and data engineering teams. Strong analytical, problem-solving, communication, and documentation skills.