Drimva

JPMorgan Chase

Senior Lead Architect: Information Architecture

Wilmington, DE +1 · Senior · Full-time · Posted Sep 22, 2026

Location
Wilmington, DE
Columbus, OH
Experience
5+ years of applied architecture experience; minimum 10 years of relevant work experience or a major role in technology implementation projects.
Education
Formal training or certification on architecture concepts; equivalent experience is not stated.

About the job

Leads information architecture and data governance for CCB Risk Technology, shaping architecture decisions and advancing data strategy and AI-enabled engineering practices.

What you'll do

  • Represent the product family in technical governance and improve architecture governance practices; contribute to architecture designs and reviews.
  • Oversee CCB Risk data governance practices and tooling, and advance the CCB Risk Data Strategy and firm-wide Data Product initiative.
  • Guide teams on shared data capabilities and AI-enabled engineering patterns, with appropriate validation, traceability, security, and handling of sensitive data.

What they ask for

  • Formal training or certification in architecture concepts and 5+ years of applied experience.
  • Minimum 10 years of relevant work experience or a major role in technology implementation projects.
  • Strong understanding of information architecture, data lineage, data management and governance; working knowledge of data catalogs and basic data modeling/meta-modeling.
  • Hands-on system design, application development, testing, and operational stability experience; advanced programming ability and deep software architecture expertise.

Nice to have

  • Knowledge of metadata management, data integration, or data migration; Databricks Lakehouse and AWS Cloud.
  • Advanced SQL; familiarity with Erwin and/or MagicDraw data modeling tools.

Tools

Databricks Lakehouse, AWS Cloud, SQL, Erwin, MagicDraw

AI focus

Uses enterprise-authorized AI in architecture analysis, decisioning, and engineering workflows, with human validation and sensitive-data safeguards; establishes reusable AI-enabled SDLC/toolchain patterns with traceability, auditability, resiliency, and security controls.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 6, 2026 (UTC)