Enterprise Data Architect
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IT/Tech
Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
Enterprise Data Architect
Location:
Charlotte, NC (Hybrid 4 days Onsite)
Compensation: $155,000 + Bonus
Duration:
Direct Hire
Work Requirements: USC and Green Card
Job SummaryThe Technology Enterprise Data Architect is a member of the Enterprise Architecture team responsible for defining and guiding enterprise-wide data architecture standards across applications, integrations, and cloud data environments.
Working closely with data platform and analytics teams, this role collaborates on data modeling approaches, warehouse design patterns, and integration strategies to help ensure enterprise data models and architectures remain consistent, interoperable, and aligned with long-term strategic direction.
This role partners with delivery teams to establish integration patterns, data modeling standards, and architectural guardrails that help guide delivery teams and vendor solutions. The Architect partners early with Solution Architects and development teams to ensure scalable, secure, and cost-effective data designs aligned with enterprise governance and modernization strategy.
The position serves as a technical advisor across major initiatives, evaluating data technologies and vendor architectures and helping teams align solutions with enterprise standards and strategic priorities. Success in this role requires strong communication and collaboration skills, the ability to translate complex architectural concepts into clear guidance for both technical and business audiences, and a strategic mindset that balances today's delivery needs with long-term sustainability and adaptability.
KnowledgeAcquired Through Education and Training
Knowledge Acquired Through Education and Training (Select the level of education required specific for the job; not the person):
Bachelor's degree (4 years)
Knowledge Acquired Through Work Experience (Select the minimum amount of RELEVANT experience required to function competently in the job): 7 or more years
List preferred qualifications. If a college degree is preferred (Associate through Doctorate), indicate the appropriate field(s) of study.List preferred qualifications. If a college degree is preferred (Associate through Doctorate), indicate the appropriate field(s) of study.:
Bachelor's degree in Computer Science, Information Systems, or related field
- Strong understanding of enterprise data architecture principles and integration patterns.
- Experience working with cloud data warehouse platforms such as Snowflake.
- Knowledge of data modeling approaches for analytical and operational workloads.
- Familiarity with modern data architectures including ELT/ETL pipelines, data lakes, distributed data systems, and architectures that support AI and advanced analytics.
- Experience integrating enterprise applications and vendor platforms through scalable data patterns.
- Ability to evaluate emerging technologies and align them with enterprise architecture strategy.
- Strong collaboration skills across architects, development teams, and data platform teams.
- Exceptional communication skills with the ability to explain complex architectural concepts to both technical teammates and business stakeholders.
- Strategic mindset with the ability to design solutions that meet current needs while remaining adaptable to future technology and business changes.
- Define and evolve enterprise data architecture standards across applications, integrations, and cloud data environments.
- Establish recommended integration patterns that support consistent and scalable data exchange between systems and vendors.
- Develop and share data modeling guidance and best practices for the enterprise cloud data warehouse (e.g., Snowflake).
- Partner with Solution Architects and development teams early in the design process to help ensure sound data and integration architecture.
- Collaborate closely with data platform and analytics teams on enterprise data modeling approaches, warehouse design patterns, and data architecture standards.
- Provide architectural guidance for data design considerations across major technology initiatives.
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