Senior Data Modeler

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 organizations 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.