Data Modeler - Remote / TelecommuteCynet Systems • Long Beach, CA
Data Modeler - Remote / Telecommute
Cynet Systems • Long Beach, CA
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[job_card.full_time]
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Job Description:
Pay Range: $48hr - $52hr
Responsibilities:
Design, develop, and maintain logical and physical data models to support enterprise applications.
Collaborate with business analysts, architects, and developers to translate business requirements into robust, scalable data structures.
Ensure data integrity, normalization, and optimization for performance, reliability, and scalability.
Work closely with ETL developers and data engineers to implement data models within enterprise data warehouses, data lakes, and operational systems.
Document data models, relationships, business rules, and metadata in alignment with enterprise architecture and compliance standards.
Participate in data governance initiatives, ensuring adherence to security, privacy, and compliance requirements, especially for PHI/PII in a healthcare environment.
Conduct data profiling, assess source system quality, identify data issues, and define data quality (DQ) rules and transformation logic.
Required Skills:
5+ years of experience in data modeling, data architecture, or database design roles.
Strong expertise in data modeling tools such as ERwin, PowerDesigner, or equivalent.
Proficiency with SQL-based databases (e.g., Oracle, SQL Server, PostgreSQL).
Solid understanding of data warehousing concepts, dimensional modeling, normalization techniques, and relational data structures.
Familiarity with the Azure Cloud platform and modern data architectures including Data Lakes and Enterprise Data Hubs (EDH).
Ability to interpret business requirements and convert them into technical specifications and actionable data model designs.
Understanding of API integration and common data exchange formats such as JSON and XML.
Excellent communication and collaboration skills for working with cross-functional business and technical teams.
Preferred Qualifications:
Experience with healthcare payer data domains such as claims, provider, and member data.
Exposure to data governance frameworks and Master Data Management (MDM) solutions.
Proficiency in performance tuning, query optimization, and designing high-performance data structures.
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