Data Warehouse Architect

EGS•Las Vegas, NV

About The Position

We are looking for a hands-on Data Warehouse Architect to lead the design and implementation of enterprise data warehouse solutions. The role defines enterprise data models, develops logical and physical schemas, creates architecture and design documentation, and implements tabular data models using Microsoft SQL Server and SQL Server Analysis Services (SSAS). This is a long-term contract position. Applicants must be U.S. citizens.

Requirements

At least 8 years of experience in data warehousing, BI architecture, or enterprise data modeling.
Hands-on experience with Microsoft SQL Server for data warehouse design and schema development.
Experience with cloud data warehousing, such as Azure Synapse, Fabric, or Snowflake.
Strong proficiency with SSAS Tabular Models, DAX, and MDX.
Expertise in enterprise data models, dimensional modeling (Kimball/Inmon), and schema design.
Skill in developing and maintaining architecture and design documentation.
Strong SQL and performance tuning skills.
Familiarity with ETL processes and tools such as SSIS and Azure Data Factory.
Must be a U.S. citizen.

Nice To Haves

Knowledge of data governance, master data management, and data security practices.
Experience with Power BI or other reporting tools integrated with SSAS tabular models.
Experience with entity relationship diagramming tools such as ER/Studio or Erwin.

Responsibilities

Define and maintain the enterprise data model in alignment with business objectives and data strategy.
Design and implement star and snowflake data warehouse schemas in Microsoft SQL Server, ensuring performance, scalability, and maintainability.
Create and maintain architectural documentation, including data flow diagrams, data dictionaries, schema designs, and design patterns.
Develop tabular models in SQL Server Analysis Services (SSAS) to support advanced analytics and reporting.
Collaborate with stakeholders, BI developers, data engineers, and business analysts to gather requirements and translate them into data architecture designs.
Ensure consistency and data integrity across source systems, staging layers, data marts, and reporting layers.
Lead and participate in data modeling, metadata management, and data quality initiatives.
Drive data architecture best practices, governance, and standards across the organization.
Provide technical leadership and mentorship to the data and analytics team.