Role: Data Architect
Location: Irving, TX/Charlotte, NC (3 days onsite per week)
Duration: 6+ Months
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:
- 15+ 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: (moved from required for
- 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 AI, machine learning, feature engineering, model training, retrieval-augmented generation, vector search, and analytical workloads
- Experience developing reference architectures, reusable design patterns, platform standards, technical guardrails, and implementation blueprints