Enterprise Data Architect – Snowflake, Data Integration & Architecture Governance

Axiom Path•Charlotte, NC

18h•Onsite

About The Position

The Enterprise Data Architect will help strengthen data architecture, modernize cloud platforms, and enable effective use of data across the business. As part of the Enterprise Architecture team, the role establishes technology standards, improves system interoperability, and guides investments in scalable, secure, future-ready solutions. The position works collaboratively with Enterprise Architects, Solution Architects, data engineering teams, analytics professionals, and business stakeholders on enterprise-wide technology decisions. The architect defines and improves enterprise data architecture principles, standards, and design guidelines across applications, cloud platforms, and integration environments. The role provides architectural direction for cloud data warehouses such as Snowflake, establishes reliable integration patterns, guides enterprise data modeling, and supports data lakes, ETL/ELT pipelines, distributed data environments, and AI-enabled analytics. It also contributes to architecture reviews and governance, evaluates technologies and vendors, and communicates recommendations to technical teams, business partners, and executives. This is an onsite role in Charlotte, North Carolina, offered as a contract-to-hire opportunity. The initial engagement is approximately 3–6 months, with potential conversion to a permanent position.

Requirements

8+ years of experience in data architecture, enterprise architecture, data engineering, or closely related technology disciplines.
Bachelor's degree in Computer Science, Information Systems, or a related field.
Demonstrated experience designing enterprise data architectures, including data models, integration patterns, and cross-platform data flows.
Strong knowledge of cloud-based data platforms and modern data warehouse architecture, with experience in Snowflake or comparable technologies.
Understanding of conceptual, logical, and physical data modeling for analytical and operational environments.
Experience establishing architecture standards, design principles, or governance practices used by multiple development or technology teams.
Knowledge of enterprise integration approaches, data pipelines, ETL/ELT processing, and distributed data architectures.
Ability to evaluate competing technologies and recommend options based on scalability, security, cost, technical complexity, and business value.
Experience collaborating with Solution Architects, software engineers, data platform teams, and business stakeholders.
Strong communication and presentation skills, including the ability to explain architectural tradeoffs to nontechnical decision-makers.
Strategic thinking and practical judgment to guide implementation teams toward sustainable solutions.

Nice To Haves

Hands-on architectural experience with Snowflake or similar enterprise cloud data warehouse platforms.
Experience supporting advanced analytics, AI-ready data environments, or enterprise data modernization initiatives.
Familiarity with formal Enterprise Architecture governance and technology review processes.
Experience influencing architecture decisions across multiple concurrent initiatives in a large enterprise.
Background evaluating vendor technologies and promoting organization-wide adoption of architectural standards.

Responsibilities

Define and continuously improve enterprise data architecture principles, standards, and design guidelines across applications, cloud platforms, and integration environments.
Establish scalable integration patterns for consistent, secure, and reliable data exchange between enterprise applications, internal platforms, and third-party solutions.
Provide architectural direction for cloud data warehouse environments, including Snowflake, emphasizing data modeling, performance, scalability, and maintainability.
Partner with Solution Architects, developers, and data engineering teams during early solution design to identify risks, evaluate alternatives, and align decisions with enterprise standards.
Guide development of enterprise data models for operational reporting, advanced analytics, and evolving business requirements.
Evaluate modern data technologies, integration platforms, and vendor solutions for architectural fit, long-term value, and alignment with modernization objectives.
Help establish architectural approaches for data lakes, ELT/ETL pipelines, distributed data environments, and AI-enabled analytics.
Participate in architecture reviews and governance discussions, recommending solutions that balance business needs, security, scalability, and cost.
Translate architectural concepts into clear recommendations for technical teams, business partners, and executive stakeholders.
Promote adoption of enterprise architecture standards through collaboration, technical guidance, mentorship, and stakeholder engagement.
Support multiple strategic technology initiatives while tracking architectural deliverables, dependencies, and implementation progress.