Principal Architect - Data

Drive the future of enterprise data at one of the world's most influential financial institutions - where your architectural decisions determine how data is produced, governed, and consumed at scale, and where strategy without execution is not enough.

As a Principal Architect at JPMorganChase within Foundational Services, you will establish a practical, enterprise-grade data architecture discipline that enables product teams to consistently produce, manage, integrate, and consume data across the organization.

This role is not limited to producing strategy, selecting governance tools, or reviewing designs after the fact - you are accountable for making data architecture executable.

You will translate standards into usable engineering patterns, help teams adopt them in live delivery, and resolve cross-product data decisions that individual teams cannot settle alone.

Foundational Services is a critical platform organization within JPMorganChase, responsible for the shared capabilities, integrations, and data infrastructure that product teams depend on.

You will partner closely with a Principal Data Modeler and a broad set of architects, engineers, and product teams - setting direction, making cross-product decisions, securing executive alignment, and removing delivery blockers while ensuring detailed modeling is connected to delivery practices and enterprise decisions.

Job responsibilities


* Define the target-state data architecture for Foundational Services, establishing clear boundaries between systems of record, analytical data stores, caches, and derived data products, and prioritizing the highest-risk domains, systems, and integrations rather than attempting to model everything at once


* Develop a prioritized data architecture roadmap that moves teams from inconsistent, after-the-fact data design to a model-first delivery discipline, with a conceptual and logical model covering priority domains and their critical data elements delivered within the first year


* Establish reusable engineering patterns for producing, sharing, moving, storing, and consuming data - including APIs, events, streaming, batch processing, and replication - and prove those patterns in real product delivery, improving them based on what works


* Define and govern standards for data contracts, schema evolution, metadata management, lineage, data quality, retention, lifecycle management, and ownership, producing execution-ready assets - reference architectures, templates, decision trees, and implementation checklists - that allow teams to adopt patterns without designing them from scratch


* Lead enterprise data architecture decisions, including canonical data definitions, systems-of-record strategy, cross-product data semantics, and integration design, resolving conflicts that individual teams cannot settle independently and securing named ownership for critical data elements and cross-product interfaces


* Require material schema and integr...