Enterprise Data Architect

Computer Task Group, Inc•Dallas, TX

1d•Hybrid

About The Position

CTG is seeking an experienced Enterprise Data Architect to assess, design, and optimize enterprise data architecture across on-premises and hybrid environments. This role will focus on data modeling, integration, ETL/ELT architecture, metadata management, and data governance while partnering with cross-functional teams to improve enterprise data quality, scalability, and accessibility.

Requirements

SQL and NoSQL database schema analysis
Enterprise data architecture (on-premises and hybrid environments)
Conceptual, logical, and physical data modeling
ETL/ELT design and data pipeline development
Data transformation and mapping frameworks
REST, SOAP, and event stream integration
Data profiling and data quality assessment tools
Data lineage and source-of-truth tracking
Data cataloging and metadata management tools
Experience with edge application data models
Strong analytical, communication, and documentation skills
8+ years of enterprise data architecture or data engineering experience.
Proven experience designing enterprise data models and integration architectures.
Experience implementing data governance, metadata management, and data quality initiatives.
Experience working within large enterprise environments.
Ability to communicate effectively with technical and business stakeholders.
Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
Equivalent professional experience will also be considered.
Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required.

Responsibilities

Design and evaluate enterprise data architecture and integration solutions.
Analyze SQL and NoSQL database schemas and recommend improvements.
Develop conceptual, logical, and physical data models.
Design ETL/ELT processes and enterprise data pipelines.
Create data mapping and transformation specifications.
Assess and improve data quality through profiling and validation.
Document data lineage, source-of-truth, and governance standards.
Support API integrations using REST, SOAP, and event-driven architectures.
Implement metadata management and data cataloging best practices.
Analyze edge application data models and enterprise integration requirements.
Collaborate with business and technical teams to establish enterprise data standards.