Principal Architect - Data

JPMorganChase • Palo Alto, CA

2d

About The Position

As a Principal Architect within JPMorganChase’s Foundational Services organization, you will establish and execute an enterprise-grade data architecture discipline that enables product teams to produce, manage, integrate, and consume data consistently across the organization. The role combines architectural strategy with hands-on execution: translating standards into engineering patterns, supporting adoption in live delivery, and resolving cross-product data decisions that individual teams cannot settle independently.

You will define the target-state data architecture and a prioritized roadmap, establish reusable data engineering patterns and governance standards, and provide execution-ready assets such as reference architectures, templates, decision trees, and implementation checklists. You will partner with a Principal Data Modeler and work across architects, engineers, product teams, data owners, and executives to align decisions and remove delivery blockers. The role also includes assessing model and schema alignment, remediating drift, and reporting adoption, exceptions, model coverage, ownership gaps, and integrity risks to leadership.

Employment offers are contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries, under Section 19 of the Federal Deposit Insurance Act.

Requirements

• Formal training or certification in architecture concepts and 10+ years of applied experience.
• Extensive experience in data architecture, enterprise architecture, software architecture, or a comparable technical leadership role within a large, complex organization.
• Deep working knowledge of conceptual, logical, and physical data modeling, relational design, identifiers, integrity constraints, schema evolution, and data contracts.
• Experience designing and governing data integration patterns across APIs, event-driven architectures, streaming platforms, batch processing, replication, and analytical environments.
• Demonstrated ability to establish common data semantics, ownership models, and canonical definitions across multiple products, systems, and business domains, including resolving conflicting definitions across teams.
• Proven ability to turn architectural standards into implementation guidance, reusable patterns, reference designs, and delivery controls used by engineering teams.
• Experience working with legacy systems with incomplete or inconsistent models, schemas, integrations, and ownership, including reverse-engineering and remediation.
• Ability to lead through influence across engineering, architecture, product, operations, risk, and senior stakeholders; make sound decisions in ambiguous environments with incomplete information; and revise direction based on delivery evidence.
• Strong written and verbal communication skills, including explaining technical trade-offs to engineers and delivery, control, or operational risks to executives.

Nice To Haves

• Experience in financial services or another highly regulated, high-availability environment.
• Experience defining systems-of-record strategy, operational versus analytical data boundaries, and data-product ownership models.
• Experience with enterprise streaming, event-driven architecture, data platforms, metadata and lineage tooling, or data catalog capabilities.
• Experience introducing model-first design, schema governance, or data-contract practices into an established organization.
• Experience leading or mentoring data architects, data modelers, software architects, or engineering teams.
• Familiarity with data classification, privacy, retention, access control, auditability, and resiliency requirements.

Responsibilities

• Define the target-state data architecture for Foundational Services, including boundaries among systems of record, analytical data stores, caches, and derived data products, prioritizing high-risk domains, systems, and integrations.
• Develop a prioritized data architecture roadmap to move teams toward model-first delivery, including conceptual and logical models for priority domains and critical data elements within the first year.
• Establish reusable patterns for producing, sharing, moving, storing, and consuming data through APIs, events, streaming, batch processing, and replication; prove and improve those patterns in product delivery.
• Define and govern standards for data contracts, schema evolution, metadata management, lineage, data quality, retention, lifecycle management, and ownership.
• Create execution-ready architecture assets, including reference architectures, templates, decision trees, and implementation checklists.
• Lead enterprise data architecture decisions on canonical data definitions, systems-of-record strategy, cross-product data semantics, and integration design; resolve conflicts and secure named ownership for critical data elements and interfaces.
• Require material schema and integration changes to have an updated model, named owner, and approved data contract before implementation; partner with the Principal Data Modeler and product architects to keep logical and physical models synchronized.
• Establish a lightweight architecture review and exception process that supports delivery while protecting critical data decisions.
• Coach architects, engineers, product teams, and data owners on approved patterns and standards, and build executive alignment on architectural decisions.
• Assess logical-model and physical-schema alignment for priority applications and lead remediation of model and schema drift, including reverse-engineering where required.
• Report adoption, exceptions, model coverage, ownership gaps, and major integrity risks to leadership.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed