Senior Information Architect

About Northern Trust

As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world's most successful individuals, families, corporations and institutions.

Since 1889, we have aligned our efforts with our three guiding Principles That Endure:
Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide.

With more than 135 years of financial experience and over 24,000 partners, we serve the world's most sophisticated clients using leading technology and exceptional service.

The Senior Information Architect sits within Northern Trust's Information Architecture team, shaping the firm's enterprise data strategy, data modelling standards, and AI-enabled capabilities.

The role will provide design authority and governance across conceptual, logical, and physical data models, operating across the firm's cloud data platforms and contributing to AI-driven data products.

• Lead and contribute with conceptual, logical, and physical data model design aligned to the firm's data mesh and medallion architectures
• Govern and maintain the enterprise data model library in SqlDBM, enforcing naming conventions, domain standards, and versioning
• Define and steward canonical data entities and lineage across source, integration, and consumption layers
• Help with the translation of business requirements into rigorous data structures in collaboration with engineering and domain teams
• Guide teams on the design and effective use of semantic data models, including their application to agentic AI solutions

• Integrate semantic layers with business glossaries, data catalogues, and lineage tooling
• Design and maintain semantic models to support agentic-AI capabilities
• Help develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and search
• Define semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data products
• Guide and control the creation of data domains that align with the banks underlying capabilities

• Design data product schemas across Snowflake and Databricks, including Delta Lake structures and access patterns
• Define and enforce architectural guardrails for data product design, including performance, scalability, security, and cost efficiency
• Set design standards and review transformation/pipelines for compliance
• Embed data contract standards and data quality frameworks across pipeline outputs

• Leverage Snowflake Cortex / Databricks Genie (or similar) to help engineering teams deliver natural language query and LLM-augmented data products
• Utilize Git Hub Copilot (or similar) to accelerate modelling, documentation, and pipeline development
• Design and define a set of agentic skills that can be provided to implementation teams
• Contribute to the firm's AI Champion network, evaluating emerging capabilities and advising on adoption

• Act as a design authority for data architecture across teams and data domains
• Partner with enterprise, security, and risk architecture to ensure data solutions align with broader technology and regulatory standards
• Provide early-stage architectural input to initiative discovery and solution design to reduce delivery risk

• Present architecture decisions to senior stakeholders, architecture review boards, and regulatory audiences
• Support regulatory compliance through robust lineage, metadata management, and data quality evidence
• Mentor junior architects and engineers within the Information Architecture community of practice

• Proven experience in data architecture, data engineering, or information management
• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related discipline
• Proven enterprise data modelling experience at conceptual, logical, and physical levels
• Hands‑on SqlDBM experience (or equivalent modern toolset)
• Proven experience with dbt Labs
• Good Python skills, API integration, automation
• Practical Snowflake and Databricks experience…