Senior Data Modeler

Role: Senior Data Modeler

Location: Washington, DC

Duration : Long term (Onsite)

Job Description:-

• Design and Model Development: Lead the development of the conceptual, logical, and physical data models for all enterprise data systems, including RDBMS, ODS, Data Marts, and Data Lakes.
• Platform Implementation: Oversee the successful implementation of data models on target platforms (SQL/NoSQL) and ensure the translation of business requirements into structured data designs.
• Governance and Standards: Define, govern, and enforce data modeling and design standards, tools, and best practices for the enterprise data models.
• Architecture Oversight: Oversee and govern the expansion of existing data architecture, ensuring alignment with strategic data management goals.
• Data Quality & Analysis: Execute complex SQL queries for data analysis, data profiling, and validation to ensure referential integrity and data quality are consistently maintained.
• Collaboration: Work with business and application/solution teams to document data flows and develop detailed data models that support analytical and operational needs.
• Risk Mitigation: Proactively identify and articulate issues and challenges in data design to reduce risks and ensure data structure scalability and optimization.
• Optimization: Drive the optimization of data query performance across platforms via model tuning and best practices implementation.

Qualifications:

• Extensive experience in developing and implementing conceptual, logical, and physical data models.
• Proven ability to work independently and collaboratively in a fast-paced environment, taking ownership of complex data initiatives.
• Expert-level experience in writing and optimizing SQL queries for data analysis, profiling, and integrity checks.
• In-depth knowledge of various data platforms, including RDBMS, Operational Data Stores (ODS), Data Marts, and Data Lakes.
• Experience with dimensional modeling (e.g., star schema, snowflake schema) and techniques for both relational and NoSQL platforms.
• Strong understanding of core data management concepts, including metadata management, data warehousing, and data lineage.
• Excellent communication and documentation skills, with the ability to translate complex data design concepts to both technical and non-technical stakeholders.