Data Modeler

This role is for a "Senior Data Modeler" in Richmond, VA, lasting 6+ months at a pay rate of "TBD". Requires 10 years of experience in data modeling, data governance, and cloud data management, with expertise in SQL, Python, and Azure technologies.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
🗓️ - Date discovered
January 18, 2025
🕒 - Project duration
More than 6 months
🏝️ - Location type
On-site
📄 - Contract type
Unknown
🔒 - Security clearance
Unknown
📍 - Location detailed
Richmond, VA
🧠 - Skills detailed
#Conceptual Data Model #Data Architecture #Physical Data Model #Scala #Data Management #Metadata #Snowflake #Data Privacy #Compliance #MDM (Master Data Management) #Databricks #Data Reconciliation #Data Quality #Data Profiling #Azure #Security #Python #SQL (Structured Query Language) #R #SQL Server #Data Security #Disaster Recovery #Cloud #Data Design #Synapse #DMP (Data Management Platform) #Data Accuracy
Role description
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End Client: State of Virginia

Job Title: Senior Data Modeler

Duration: 06+ Months

Start Date: ASAP

Location: Richmond, VA 23219

Position Type: Contract

Interview Type: In-Person Interview Only

Requirement ID: SVA_DATA577_VV

Position #: VDOT Enterprise Data Modeler (752577)

Required Skills:

10 Years of Create conceptual data model to identify key business entities and visualize their relationships, define concepts and rules.

10 Years of Translate business needs into data models Build logical and physical data models for client hierarchy Document data designs for team.(Required)

10 Years of Present and communicate modeling results and recommendations to internal stakeholders and Development teams and explains features that may affect

10 Years of Develop canonical models, Data as a service models and Knowledge of SOA to support integrations.(Required)

10 Years of Perform data profiling/analysis activities that helps to establish, modify and maintain data model (Required)

10 Years of Analyze data-related system integration challenges and propose appropriate solutions with strategic approach. (Required)

10 Years of Perform data profiling and analysis for maintaining data models Develop and support the usage of MDM toolkit Integrate source systems into the MDM sol (Required)

10 Years of Implement business rules for data reconciliation and deduplication Enforce data models and naming standards across deliverables.(Required)

10 Years of Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity.(Required)

10 Years of Establish methods and procedures for tracking data quality, completeness, data redundancy, and improvement.

Required

10 Years of Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks.(Required)

Department: The Virginia Department of Transportation (VDOT)
• local Richmond, VA candidates required
• candidate will be required to interview ONSITE, NO exceptions
• candidate will be required to work ONSITE 2-3 days/wk
• the contract may be extended annually beyond June 30, 2025
• Contractor will be responsible for purchasing parking through VDOT’s Parking Management Office or procuring their own parking

Job Description: Enterprise Data Modeler

The Virginia Department of Transportation (VDOT) Information Technology Division is seeking a senior Data modeler to develop Data models for Data Assets and implementation of a cloud-based data management platform that will support the agency.

Enterprise data modeler provides expert support across the enterprise information framework, analyze and translate business needs into long-term solution data models by evaluating existing systems and working with a business and data architect to create conceptual data models , data flows . Develop best practices for Data Asset development, ensure consistency within the system and review modifications of existing cross-compatibility systems. Optimize data systems and evaluate implemented systems for variance discrepancies and efficiency. Maintain logical and physical data models along with accurate metadata.

Responsibilities:
• Create conceptual data model to identify key business entities and visualize their relationships, define concepts and rules.
• Translate business needs into data models Build logical and physical data models for client hierarchy Document data designs for team.
• Present and communicate modeling results and recommendations to internal stakeholders and Development teams and explains features that may affect the physical data model.
• Ensure and enforce a governance process to oversee implementation activities and ensure alignment to the defined architecture.
• Perform data profiling/analysis activities that helps to establish, modify and maintain data model.
• Develop canonical models, Data as a service models and Knowledge of SOA to support integrations.
• Analyze data-related system integration challenges and propose appropriate solutions with strategic approach.
• Perform data profiling and analysis for maintaining data models Develop and support the usage of MDM toolkit Integrate source systems into the MDM solution Implement business rules for data reconciliation and deduplication Enforce data models and naming standards across deliverables.
• Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity.
• Establish methods and procedures for tracking data quality, completeness, data redundancy, and improvement.
• Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks.
• Create strategies and plans for data security, backup, disaster recovery, business continuity, and archiving.· Ensure that data strategies and architectures are in regulatory compliance.
• Good knowledge of applicable data privacy practices and laws.
• Strong written and oral communication skills. Strong presentation and interpersonal skills and Ability to present ideas in user-friendly language.
• Experience in writing queries (SQL, Python, R, Scala) as needed and experience with various data technologies such as Azure Synapse or SQL Server, Snowflake, Databricks