Principal Data Architect Chief Data Office

Wells Fargo is seeking a Principal Data Architect— a hands-on technologist who will shape modern data architecture across cloud and on-prem environments in a large-scale banking ecosystem. This role designs scalable patterns for application, analytics, workflow, and AI-enabled workloads while guiding the evolution of legacy systems into secure, resilient, and future-ready platforms.  The ideal candidate balances strategy, design, and hands-on execution—proving concepts through code, solving complex data challenges, and influencing senior technologists. You will work across diverse systems, define architectural patterns, and enable teams to modernize data environments with practical, AI-aware solutions.

This role requires deep expertise in distributed data systems, application and workflow integration, and analytic platforms, along with the ability to translate current-state constraints into forward-looking architectures. Experience using both traditional development and AI-assisted engineering tools is key.  Beyond technical leadership, you will mentor teams, align architecture to business outcomes, and communicate effectively with both technical and business stakeholders. Success in this role requires driving solutions that balance innovation with measurable value, including considerations of scalability, cost (TCO), and ROI.

 
In this role, you will: 

Act as an advisor to senior leadership to develop the architectural framework & delivery for highly complex business and technical needs across multiple groups 

Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering products and solutions that are long-term, large-scale, and require vision, creativity, innovation, advanced analytical and inductive thinking 

Provide vision, direction, and expertise to senior leadership on implementing the transformation strategy describing the current state, target state, and transition architecture 

Develop and influence strategic plans, investment planning, and execution on cutover strategies to target 

Strategically engage with all levels of professionals and managers across the enterprise and serve as an architectural domain expert advisor to leadership  

Drive target investments towards target technologies and rationalize spend, total cost of ownership, and return on investment 

Ensure applications adhere to established Wells Fargo standards, policies, methodologies, and industry best practices as it transforms toward target state architecture 

Drive the definition, establishment, selection of strategic tools, and application of architecture frameworks 

Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization and can influence internal and vendor roadmaps in a significant capacity 

Required Qualifications: 

• 7+ years of experience in data architecture, data engineering, database platforms, or enterprise technology roles, with significant experience in large-scale financial services or banking environments. 
• 7+ years of designing enterprise-scale data architectures across hybrid cloud, public cloud, private cloud, and on-premises platforms. 
• 7+ years of experience with relational, NoSQL, columnar, distributed, and shared-nothing database technologies. 

Desired Qualifications: 

• Proven ability to design scalable architectures using partitioning, sharding, replication, workload isolation, horizontal scaling, and distributed processing patterns
• Experience architecting batch, streaming, event-driven, real-time, near-real-time, and API-based data integration patterns
• Strong understanding of how application workloads, analytical workloads, reporting workloads, workflow engines, and AI/ML workloads interact with enterprise data platforms
• Hands-on capability with technologies such as SQL, Python, Java, Spark, Kafka, Airflow, APIs, and modern data pipeline frameworks
• Expertise in data modeling, including conceptual, logical, physical, dimensional, canonical, domain-driven, and event-based models
• Strong knowledge of data security architecture, including encryption, tokenization, masking, access controls, entitlement models, secrets management, and audit logging
• Ability to define and evaluate non-functional technical requirements, including latency, throughput, scalability, availability, resiliency, recovery, observability, security, and maintainability
• Familiarity with designing data architectures that support