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 modeling 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 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.
Required Skills :
Basic Qualification :
Additional Skills :
This is a high PRIORITY requisition. This is a PROACTIVE requisition
Background Check : No
Drug Screen : No
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 mode...
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 modeling 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 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.
Required Skills :
Basic Qualification :
Additional Skills :
This is a high PRIORITY requisition. This is a PROACTIVE requisition
Background Check : No
Drug Screen : No
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