Enterprise Data Modeler

Job Title: Enterprise Data Modeler

Location: Richmond, VA (Hybrid 2 3 days onsite per week)
Contract Duration: Through June 30, 2026 (with potential annual extensions)
Interview Process: Phone and In-person (Onsite interview required)
Local Richmond area candidates highly preferred
Note: Contractor is responsible for parking arrangements.

Position Overview

We are seeking a highly experienced Enterprise Data Modeler to design and optimize data models, frameworks, and standards to support a large-scale cloud-based data management platform. This role requires senior-level expertise in enterprise data modeling, data integration, governance, and metadata management. The ideal candidate will bridge business needs with technology solutions by creating conceptual, logical, and physical data models while ensuring accuracy, compliance, and scalability.

Responsibilities

Develop conceptual data models to identify key business entities and relationships, define business rules, and ensure alignment with organizational strategy.

Translate business needs into logical and physical data models and produce detailed documentation for technical teams.

Present and clearly communicate modeling results, data recommendations, and impacts to stakeholders and development teams.

Establish and enforce governance processes to ensure alignment with enterprise architecture.

Perform data profiling and analysis to maintain and refine data models.

Develop canonical models and Data-as-a-Service (DaaS) models; utilize SOA principles to support integrations.

Analyze and resolve complex data-related system integration challenges with a strategic approach.

Support Master Data Management (MDM) initiatives including reconciliation, de-duplication, and standard enforcement.

Establish processes for monitoring data quality, accuracy, completeness, and redundancy improvements.

Build strategies for data governance, metadata management, archiving, and regulatory compliance.

Guide policies for data security, backup, disaster recovery, and business continuity.

Collaborate with teams to ensure enterprise data assets follow best practices, standards, and consistent usage.

Write advanced queries (SQL, Python, R, Scala) and work with data environments such as Azure Synapse, SQL Server, Snowflake, and Databricks.

Required Skills & Experience

10+ years creating conceptual, logical, and physical data models.

10+ years presenting and communicating data models and solutions to stakeholders.

10+ years working on canonical models, DaaS, and SOA-based integrations.

10+ years in data profiling, analysis, and Master Data Management (MDM).

10+ years establishing governance processes for metadata and data quality.

10+ years conducting data capacity planning, lifecycle management, and optimization.

Strong understanding of data privacy practices and compliance laws.

Proficiency in SQL and scripting languages (Python, R, Scala).

Hands-on experience with Azure Synapse, SQL Server, Snowflake, and Databricks.

Excellent communication, presentation, and interpersonal skills.

Work Arrangement

Hybrid schedule: 2 3 days onsite per week.

Onsite interviews are mandatory (no exceptions).