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Ai Data Architect Jobs in Raleigh, NC (NOW HIRING)

First Citizens Bank

Senior Data Architect

Raleigh, NC · On-site

$65.25 - $87.50/hr

Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases. * Drive consistency across data acquisition, storage, transformation, governance, and consumption ...

First Citizens Bank

Senior Data Architect

Raleigh, NC · On-site

$65.25 - $87.50/hr

Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases. * Drive consistency across data acquisition, storage, transformation, governance, and consumption ...

First Citizens Bank

Senior Data Architect

Raleigh, NC

$65.25 - $87.50/hr

Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases. * Drive consistency across data acquisition, storage, transformation, governance, and consumption ...

First Citizens Bank

Senior Data Architect

Raleigh, NC

$65.25 - $87.50/hr

Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases. * Drive consistency across data acquisition, storage, transformation, governance, and consumption ...

Thermo Fisher Scientific

Sr Staff AI Architect

Raleigh, NC · On-site +1

$143K - $185K/yr

The AI & Data Architect will define and govern the technical blueprint for enterprise AI and data ecosystems. This role ensures solutions are scalable, secure, reusable, and aligned with enterprise ...

Infosys

Data Bricks AI/ML Technical Architect

Raleigh, NC · On-site

$62 - $79.75/hr

In the assigned Job Role of Architecture Consultant 2, your Area Of Responsibility will be as below ... power of data and AI. At Infosys DNA, you'll have the opportunity to work with cutting-edge ...

Infosys Limited

AWS Redshift Data Architect

Raleigh, NC · On-site

$110 - $170/hr

Our AI-driven solutions empower financial institutions to make smarter decisions, enhance customer ... In the assigned Job Role of Architecture Consultant 2, your Area Of Responsibility will be as below:

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Ai Data Architect information

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How much do ai data architect jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for ai data architect in Raleigh, NC is $68.02, according to ZipRecruiter salary data. Most workers in this role earn between $59.57 and $76.63 per hour, depending on experience, location, and employer.

What is an AI data architect?

An AI Data Architect is a professional who designs, builds, and manages the data infrastructure necessary for artificial intelligence (AI) and machine learning (ML) systems. They ensure that data is collected, stored, processed, and made accessible in a way that supports AI applications. Their responsibilities include selecting appropriate data storage solutions, creating data models, establishing data pipelines, and maintaining data quality and security. AI Data Architects work closely with data scientists, engineers, and business stakeholders to translate business needs into robust data solutions that enable AI-driven insights and automation.

How does an AI data architect typically collaborate with data engineers, data scientists, and other stakeholders within an organization?

An AI Data Architect plays a central role in bridging the gap between data engineering, data science, and business stakeholders. They design and oversee the data infrastructure required for AI applications, working closely with data engineers to ensure pipelines are scalable and secure. In collaboration with data scientists, they help define data requirements and optimize data flows for model training and deployment. Frequent communication with product managers and business leaders helps align the data architecture with organizational goals and regulatory standards, making adaptability and strong interpersonal skills key components of the role.

What are the key skills and qualifications needed to thrive as an AI data architect, and why are they important?

To thrive as an AI Data Architect, you need deep expertise in data modeling, database design, and AI/ML concepts, often backed by a degree in computer science, engineering, or a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), big data frameworks (like Hadoop and Spark), and certifications in cloud architecture or data engineering are highly valued. Strong analytical thinking, problem-solving skills, and effective communication are crucial for collaborating across teams and translating business needs into scalable data solutions. These skills ensure robust, efficient AI systems that support organizational goals and drive innovation.

What is the difference between Ai Data Architect vs Data Engineer?

AspectAi Data ArchitectData Engineer
CredentialsBachelor's/Master's in CS, Data Science, or related; certifications in cloud platforms or data architectureBachelor's/Master's in CS, Software Engineering, or related; certifications in cloud or data tools
Work EnvironmentDesigning data architecture for AI models, collaborating with data scientists and AI teamsBuilding and maintaining data pipelines, managing data storage and processing systems
Industry UsageUsed in AI-focused companies, tech firms, and organizations deploying AI solutionsCommon across industries for data management, analytics, and infrastructure

The Ai Data Architect focuses on designing data systems optimized for AI applications, working closely with data scientists. In contrast, Data Engineers build and maintain the data pipelines and infrastructure needed for data processing. Both roles require similar technical skills and certifications but serve different functions within data ecosystems.

How much do AI Data Architects make?

AI Data Architects typically earn between $100,000 and $160,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in data modeling, cloud platforms, and machine learning can command higher salaries. Certifications and a strong understanding of data management tools also influence compensation.

What does a data and AI architect do?

A data and AI architect designs and manages data systems and AI solutions to support business goals. They develop data pipelines, implement machine learning models, and ensure data security, often using tools like cloud platforms and programming languages such as Python or SQL. Strong analytical skills and knowledge of data governance are essential for this role.

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The top searched job categories for Ai Data Architect jobs in Raleigh, NC are:

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Ai Data Architect jobs near you
Infographic showing various Ai Data Architect job openings in Raleigh, NC as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $141,485 per year, or $68 per hour.

Senior Data Architect

First Citizens Bank

Raleigh, NC • On-site

$65.25 - $87.50/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

106th of 171 rated banks

Job description

Overview

The Senior Data Architect is a senior technical leader within Enterprise Data & Analytics (ED&A) responsible for defining, designing, and implementing enterprise-scale data architectures that enable trusted, governed, and business-ready data across the organization.

This role requires deep hands-on expertise across transactional systems (OLTP), analytical platforms (OLAP), modern cloud data platforms, data integration, and enterprise data modeling. The Senior Data Architect is expected to operate from strategy through implementation, partnering with engineering teams to design scalable solutions while actively participating in architecture reviews, complex data modeling, performance optimization, data product design, and platform modernization initiatives.

The ideal candidate brings extensive experience designing and implementing modern data ecosystems leveraging AWS, Snowflake, Data Vault 2.0, DBT, API-based integration patterns, event-driven architectures, metadata management, and AI-ready data foundations.


Responsibilities
Enterprise Data Architecture & Design
  • Define and evolve enterprise data architecture standards, patterns, and reference architectures.
  • Develop target-state architectures supporting ED&A strategic objectives and Nexus platform evolution.
  • Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases.
  • Drive consistency across data acquisition, storage, transformation, governance, and consumption layers.
  • Establish architecture guardrails balancing agility, scalability, maintainability, and regulatory compliance.
Modern Data Platform Architecture

Serve as a senior technical architect responsible for end-to-end design of the Nexus ecosystem including:

Data Ingestion Layer
  • Qlik Replicate and CDC patterns
  • Event-driven ingestion architectures
  • API-driven integrations
  • Batch and near real-time ingestion frameworks
  • External and third-party data integration
Data Storage & Processing Layers
  • AWS S3 data lake architecture
  • Landing and ingestion zones
  • Snowflake data platform architecture
  • Raw Data Vault implementation
  • Business Data Vault design
  • Consumption and semantic layers
  • Data sharing and data product architectures
Transformation & Orchestration
  • DBT architecture and modeling standards
  • ELT pipeline design
  • Reusable transformation frameworks
  • Astronomer (Airflow) orchestration patterns
  • Workflow dependency management
  • Data observability and monitoring
Operational Analytics
  • API-enabled data products
  • Fargate-based services
  • Near real-time analytics solutions
  • Event streaming architectures
  • Operational reporting architectures
Enterprise Data Modeling Leadership

Provide deep expertise across multiple modeling disciplines:

OLTP Modeling
  • Third Normal Form (3NF)
  • Operational application schemas
  • Transaction processing systems
  • Customer, account, loan, and transaction data structures
  • Source system integration patterns
Analytical Modeling (OLAP)
  • Star schemas
  • Snowflake schemas
  • Fact and dimension design
  • Aggregate layer strategies
  • Semantic modeling
Data Vault 2.0
  • Hubs
  • Links
  • Satellites
  • Business Vault design
  • Point-in-time structures
  • Bridge tables
  • Auditability and lineage patterns
Information Architecture
  • Enterprise canonical models
  • Business capability mapping
  • Customer 360 architectures
  • Reference and master data design
  • Domain-driven architecture
  • Architects in this role are expected to actively review and contribute to data models rather than simply approve designs.
Data Products & Domain Architecture
  • Drive adoption of data product thinking across ED&A.
  • Define standards for ownership, accountability, quality, discoverability, and reuse.
  • Partner with business domains to establish trusted and reusable analytical assets.
  • Design scalable domain-oriented architectures supporting Data Mesh principles where appropriate.
  • Enable self-service consumption through governed data products.
Data Governance by Design

Partner closely with Governance teams to embed controls directly within architectural designs.

Responsibilities include:

  • Metadata architecture
  • Business glossary alignment
  • Technical and business lineage
  • Data quality architecture
  • Data contract implementation
  • Sensitive data classification
  • Policy-based access control
  • Data retention and auditability
  • Leverage Collibra, BigID, and platform-native capabilities to improve trust and transparency across enterprise data assets.
Performance Optimization & Engineering Excellence

Actively troubleshoot and improve platform performance by:

  • Reviewing Snowflake query performance
  • Optimizing warehouse utilization and workload management
  • Designing scalable partitioning and clustering strategies
  • Improving ELT processing efficiency
  • Reducing data movement and duplication
  • Enhancing pipeline scalability and resiliency
  • Ensuring efficient storage and compute utilization
  • Expected to participate in technical deep-dives and solution reviews with engineering teams.
AI & Advanced Analytics Architecture
  • Define architectural foundations for enterprise AI initiatives.
  • Design AI-ready data products and curated consumption layers.
  • Support feature engineering and model-serving architectures.
  • Enable trusted, explainable, and governed AI data pipelines.
  • Partner with Data Science teams to ensure scalability of predictive and generative AI solutions.
  • Architect retrieval, metadata, and knowledge-layer capabilities supporting future GenAI initiatives.
Technical Leadership
  • Lead architecture reviews across strategic initiatives and programs.
  • Influence technical direction across engineering, analytics, governance, and business teams.
  • Mentor engineers, architects, and modelers on modern architecture principles.
  • Establish engineering standards, design patterns, and reusable frameworks.
  • Provide thought leadership on emerging technologies and industry best practices.
  • Serve as the escalation point for complex architecture and modeling challenges.

Qualifications

Bachelor's Degree and 6 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms OR High School Diploma or GED and 10 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms

Preferred Qualifications

  • Financial Services or Banking industry experience.
  • Experience modernizing legacy data warehouse environments.
  • Experience architecting large-scale Customer 360 solutions.
  • Experience supporting regulatory and risk reporting ecosystems.
  • Knowledge of Data Mesh and Data Product operating models.
  • TOGAF, CDMP, SnowPro, AWS, or equivalent certifications.
Experience
  • 12+ years of experience in Data Engineering, Data Architecture, Information Management, or Analytics Engineering.
  • 5+ years serving as a lead architect for enterprise-scale data platforms.
  • Proven experience designing and implementing modern cloud data platforms.
  • Demonstrated experience leading large-scale data modernization programs.
  • Experience working directly with engineering teams on implementation, optimization, and troubleshooting.
Modern Data Platforms
  • Snowflake
  • AWS Data Services
  • Amazon S3
  • Data Lake and Lakehouse architectures
  • Cloud-native data ecosystems
Data Engineering
  • ELT/ETL architectures
  • Data integration patterns
  • Change Data Capture (CDC)
  • Event-driven architectures
  • API-based integration
  • Data orchestration frameworks
Nexus Core Technologies
  • Snowflake
  • DBT
  • Qlik Replicate
  • Astronomer / Apache Airflow
  • AWS
  • Data Vault 2.0
  • Collibra
  • BigID
Data Modeling
  • Conceptual, Logical and Physical Data Modeling
  • Data Vault 2.0
  • Dimensional Modeling
  • Canonical Modeling
  • Master Data Management
  • Reference Data Management
Data Management
  • Data Governance
  • Data Quality
  • Data Lineage
  • Metadata Management
  • Data Cataloging
  • Data Contracts

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

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