The Enterprise Data Architecture team is a central organization responsible for defining the enterprise-wide data standards, architectural patterns, and foundational capabilities that enable scalable, trusted, and reusable data solutions across the firm. Working closely with Enterprise Architecture and partners across business and technology, this team helps shape how data is structured, governed, and leveraged to support innovation, operational excellence, and informed decision-making.
This team plays a critical role in advancing the firm’s data strategy by establishing the architectural foundation for high-quality, well-governed, and compliant data products at enterprise scale. In addition to driving consistency and control in how data is managed, the team is helping enable the firm’s broader modernization efforts through cloud-native data architecture and the evolving use of AI-powered capabilities. As the organization expands its use of AI, strong information architecture and data modeling practices are increasingly essential to ensuring data is discoverable, trusted, interoperable, and fit for intelligent applications across the enterprise.
Role Summary
As a Senior Enterprise Information Architect, you will play a key role in shaping the firm’s enterprise information architecture through leadership in building enterprise logical and physical data models aligned to an enterprise data product strategy. You will be responsible for defining, governing, and evolving core data models that support enterprise data products and scalable business capabilities across the organization.
This role requires deep expertise in data modeling practices, a strong understanding of enterprise data architecture, and the ability to collaborate effectively across a wide range of stakeholders. You will help design data structures that not only support current business needs but also position the firm for future growth in cloud-based data platforms, advanced analytics, and AI-enabled solutions.
We are seeking an energetic, creative, and highly collaborative architect who enjoys solving complex data challenges and designing scalable capabilities that can be adopted across the enterprise. This is an opportunity to influence foundational architecture in an environment where trusted data is increasingly central to digital transformation, intelligent automation, and responsible AI adoption.
Responsibilities
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Take accountability for individual deliverables and, at times, provide guidance to others by offering process and standards advice within your area of specialization
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Understand, apply, and advocate for Enterprise Architecture principles, clearly articulating the value of architecture to technology and business partners
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Manage and continuously improve the design and implementation of architecture processes, standards, and artifacts
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Review key design decisions with departmental architecture review boards and help guide sound architectural outcomes
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Ensure architecture decisions are made in alignment with standards, and that deviations are properly identified, assessed, documented, and communicated; escalate issues to Principal Architects and Senior Managers as needed
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Participate in and lead reviews of in-flight projects, working closely with technical leads to address complex design challenges and provide hands-on support where needed
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Ensure solution architecture artifacts and related changes are documented according to process standards and maintained in the T. Rowe Price EA Library to support compliance, transparency, and reuse
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Coordinate with other enterprise architects as needed to align solution architecture with broader enterprise direction
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Bring structure and clarity to complex or ambiguous problems, working through them in a rational and practical way
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Balance tactical needs with strategic goals when evaluating trade-offs and recommending solutions
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Demonstrate flexibility in thinking and adapt architectural recommendations as new information or perspectives emerge
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Contribute to continuous improvement by recommending enhancements to team practices, standards, and ways of working
Qualifications
Required:
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Bachelor’s or Master’s degree in a technical field, or the equivalent combination of education and relevant experience, along with 5+ years of experience in data-intensive roles
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Proven track record of defining, implementing, and sustaining conceptual, logical, and physical data models for enterprise data products
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Demonstrated ability to establish, socialize, and govern enterprise standards for data modeling practices aligned with a target information architecture
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Hands-on experience designing effective, scalable, and high-performing data models for both structured and unstructured data in modern cloud data ecosystems such as Snowflake and AWS
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Strong expertise in data mapping, lineage, classification, cataloging, and the application of enterprise-wide data standards and controls
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Creative thinking in using AI capabilities to drive efficiency and accuracy for building data assets and collecting/storing context
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Working alongside our Data Governance team, DG tools and practices to ensure data context.
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Deep passion for data modeling and information architecture, with a strong belief in the value of well-structured data to improve understanding, reuse, and business outcomes
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High level of proficiency with data modeling tools such as SQLDBM, Hackolade, or similar technologies, including management of a central enterprise model repository
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Strong collaboration and communication skills, with the ability to engage effectively with both technical and non-technical stakeholders
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Experience supporting data architecture that enables advanced analytics, AI applications, or intelligent data products, with an understanding of the importance of trusted, well-governed, and reusable data foundations
Preferred:
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5+ years of Data Architecture experience in Asset Management or a related financial services industry
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Experience working in highly regulated, data-intensive environments with strong governance, risk, and control expectations
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Familiarity with data architecture patterns that support AI/ML use cases, semantic consistency, and enterprise-scale information reuse
FINRA Requirements
FINRA licenses are not required and will not be supported for this role.
Work Flexibility
This role is eligible for hybrid work, with up to three days per week from home.
