Data Modeler at Amtex Systems Inc. in Atlanta, Georgia

Job Description:

• Strong understanding of Data Warehouse concepts (ETL, Star Schema, slowly changing dimensions)
• Strong knowledge of relational databases, Data Warehouse, and business Intelligence solutions
• Excellent teamwork and collaboration skills
• Understand existing data model, collaborate with client business & technical teams to develop the target state data model
• Develop Logical, Physical data models and build tables, indexes, database objects

• Develop, maintain, and enhance conceptual, logical, and physical data models for various business domains and applications.
• Experience in building Data models in OLTP Systems from the scratch.
• Experience in building generic DATA models for File Processing, Document Processing, Hierarchy models, Data Auditing, Notifications.
• Translate business requirements into data models ensuring structural integrity and compliance with organizational standards.
• Design and optimize database structures to support data storage, retrieval, and analysis.
• Collaborate with database administrators and developers to implement data models in database systems (SQL Server, Oracle).
• Ensure data integrity, security, and performance through proper database design and optimization techniques.
• Perform data profiling, analysis, and validation to identify inconsistencies and anomalies.
• Collaborate with stakeholders to elicit, analyze, and document data requirements.
• Create clear and comprehensive documentation of data models, including entity-relationship diagrams, data dictionaries, and metadata.
• Support data integration projects by mapping data sources to target data models and designing data transformation processes.
• Facilitate data migration efforts, ensuring seamless transition of data from legacy systems to new platforms or environments.
• Work closely with business analysts, developers, and project managers to align data modeling efforts with project timelines and objectives.
• Conduct quality assurance reviews of data models to ensure accuracy, completeness, and usability.
• Identify and resolve data model-related issues, such as performance bottlenecks, data anomalies, and schema conflicts.
• Contribute to the overall success of the team by actively participating in meetings, sharing insights, and contributing innovative ideas.