Senior Lead Architect: Information Architecture

JPMorgan Chase & Co.•Wilmington, DE

About The Position

As a Senior Lead Architect at JPMorganChase within the Enterprise Risk Technology team of Corporate Sector, you are an integral part of a team that works to develop high-quality architecture solutions for various software applications and platforms products. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains. Provide expert knowledge of application architecture and consult to Business and Technology teams when detailed application architecture knowledge is needed, and identify/mitigate risks to delivering solution on time. You will partner with architects and cross-functional stakeholders across multiple LOBs and Corporate Functions to translate guidance from Data Strategy, Data Governance, Risk Management, and Compliance into actionable solutions for Risk Technology and Product teams.

Requirements

Formal training or certification on architecture concepts and 5+ years applied experience
Minimum 10 years of relevant work experience or played a major role in technology implementation projects.
Strong understanding of information architecture (data lineage), data management/data governance principles (data quality), and working knowledge of data catalog.
Strong communication skills and ability to partner and collaborate with different personas across multiple forums.
Ability to learn new tools, adopt new trends, and deliver strategic and tactical solutions efficiently using AI.
Basic knowledge and experience with data modeling and meta-modeling.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Advanced in one or more programming language(s) and deep expertise in software architecture, applications, and technical processes within one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
Demonstrated experience applying enterprise-authorized AI capabilities within the work environment in architecture and engineering workflows with strong validation habits and awareness of data sensitivity.

Nice To Haves

Knowledge of basic information architecture capabilities like Metadata Management, Data Integration, and Data Migration.
Knowledge of Databricks Lakehouse ecosystem and AWS Cloud platform/services.
Ability to write advanced SQL and analyze data as needed. Hands-on research using SQL and AI.
Basic knowledge of Erwin and/or MagicDraw data modeling tool to view and navigate data models if needed.
Ability to tackle design and functionality problems independently with little to no oversight.
Ability to evaluate current and emerging technologies to select or recommend the best solutions for the future state architecture.
Strong judgment and communication skills to influence technical direction across teams.

Responsibilities

Represents a product family in technical governance bodies and proposes improvements to architecture governance practices
Contribute to architecture designs and reviews, representing data governance and data management concerns.
Oversee the CCB Risk Tech data governance practices and tooling.
Interpret and drive firm-wide Data Product initiative within CCB Risk.
Collaborate with Product and Tech teams to curate and advance CCB Risk Data Strategy.
Engage to identify and support the sharing and adoption of common data-related capabilities (metadata generation, interoperability, data quality and observability, etc).
Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors.
Leverages enterprise-authorized AI capabilities within the work environment to accelerate architecture analysis and decisioning across the product family, with human-in-the-loop validation and appropriate handling of sensitive data.
Drive decisions that influence product design, application functionality, and technical operations and processes.
Establishes reuse-first AI-enabled engineering patterns and governance across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls.