Senior Data Architect

Raleigh, NC · Phoenix, AZFull-timePosted Aug 7, 2026

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.