Job Description

Job Title Senior Data Modeler

Location Washington, DC

Job Description

This Senior Data Modeler role, supporting a key Randstad client in the D.C. area, is responsible for the design, governance, and optimization of the organization's enterprise data assets. The ideal candidate will be a hands-on technical leader, architecting the conceptual, logical, and physical data models for various platforms, including traditional RDBMS, Operational Data Stores (ODS), Data Marts, and modern Data Lakes on SQL/NoSQL platforms. This role requires defining and enforcing enterprise data modelling standards and best practices, working independently to meet business requirements, and collaborating with cross-functional teams to ensure all data solutions are highly performant, scalable, and maintain data integrity across the entire data lifecycle.

Responsibilities

• 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 modelling 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 modelling (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

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