JPS Tech Solutions
Senior Data Modeler
Join to apply for the
Senior Data Modeler
role at
JPS Tech Solutions
2 days ago Be among the first 25 applicants
Job Category:
Senior Data Modeler SQL/NoSQL
Job Type:
Hybrid
Job Location:
District of Columbia Washington
Compensation:
Depends on Experience
W2:
W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.
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 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.
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Senior Data Modeler
role at
JPS Tech Solutions
2 days ago Be among the first 25 applicants
Job Category:
Senior Data Modeler SQL/NoSQL
Job Type:
Hybrid
Job Location:
District of Columbia Washington
Compensation:
Depends on Experience
W2:
W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.
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 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.
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