Principal Information Architect – Metadata Thought Leadership

Step into the role of a Principal Information Architect (Executive Director) at JPMorganChase and become a promoting force behind the development and adoption of cutting-edge, cloud-based technologies. Make metadata real, usable, and impactful in modern engineering. In this role, you’ll sit at the intersection of Information Architecture and Software Engineering—building models, languages, and tooling that help teams move faster with clarity and control. You’ll have room to grow your craft, deepen your technical breadth, and influence standards across a large, complex environment.

As a Principal Information Architect, Metadata at JPMorganChase within the Commercial & Investment Bank, you will connect enterprise modeling and metadata practices to real software engineering assets and workflows. You will develop metamodels, controlled vocabularies, mappings, lineage, and domain-specific languages that make metadata actionable. You will prototype and maintain tooling that captures, validates, transforms, and presents metadata to support current and emerging needs. You will influence direction through thought leadership (not people management), partnering with stakeholders to drive standards and adoption. You will help ensure models and metadata support development practices and regulatory asks in a clear, implementable way.
This could suit a strong Information Architect with metadata experience and an interest in software development, or a strong Software Engineer with metadata and language experience wishing to grow into an Information Architect role. It might also support someone with an academic background, with some hands-on experience.

Job responsibilities

• Develop and maintain the metamodel to support current and emerging business needs
• Create and evolve novel metadata assets, including controlled vocabulary, mapping, lineage, transformation, and data content descriptions
• Build and maintain mappings between metadata and software engineering assets
• Design and maintain domain-specific languages that represent metadata, including their underlying structures
• Prototype and maintain tooling that captures, integrates, validates, transforms, generates code from, reports on, and presents metadata
• Engage with customers, the Chief Data Office, product owners, Information Architects, development teams, and other stakeholders to communicate the Information Architecture vision and standards, and support effective implementation
• Architect metadata and language foundations that enable AI solution capabilities, including semantic consistency, provenance/lineage, policy tagging, and interoperability across engineering workflows
• Establish reuse-first, metadata-driven engineering patterns and governance that support AI-enabled platforms (e.g., traceability/auditability, resiliency, and security controls) through well-defined models, DSLs, and tooling integrations
 

Required qualifications, capabilities, and skills

• Create logical and physical data models and express them clearly for both technical and non-technical audiences
• Use UML modeling tools (for example, MagicDraw, PowerDesigner, or Eclipse-based tooling)
• Apply metamodel concepts (for example, UML and MOF) to structure and govern modeling approaches
• Work with controlled vocabularies and metadata standards to drive consistency and reuse
• Produce and interpret mappings and lineage to explain how data is related, moved, and transformed
• Translate between what is in a model and its corresponding representation in programming and schema languages. Build or maintain domain-specific languages, including their abstract syntax structures
• Program effectively in one or more languages such as Java, JavaScript, Python, or C++. Implement language tooling components such as parsers, interpreters, compilers, debuggers, or related frameworks
• Prototype solutions independently and navigate ambiguous design and functionality problems
• Collaborate with business and technical teams to understand, translate, review, and playback requirements
• Intimately understand the relationship between what is in a model and its corresponding representation in other programming and schema languages. Similarly, for domain specific languages and ASTs.
• Demonstrated experience designing metadata/language architecture that supports AI-enabled solutions, including enforceable semantics, lineage/provenance, and integration into scalable platforms with resiliency, security, and auditability requirements

• Exposure to code generation patterns and the development or use of code generators. Familiarity with data management technologies such as relational or columnar databases, data integration (ETL), or API development
• Familiarity with data formats such as JSON, XML, Avro, or Google Protocol Buffers
• Comfort engaging with the algorithms and mathematics behind languages, tooling, and data processing
• Academic background paired with hands-on implementation experience
• Interest in how strong Information Architecture and models enable modern software development and engineering discipline
• Awareness of how modeling and metadata practices support regulatory and control requirements

If you’re someone who enjoys working across modeling, metadata, languages, and software engineering—and you like bringing clarity, standards, and practical tooling to complex environments—we’d like to hear from you.