Senior Lead Data Architect

JPMorganChase•Plano, TX

About The Position

If you are excited about shaping the future of technology and driving significant business impact in financial services, we are looking for people just like you. Join our team and help us develop game-changing, high-quality solutions. You strive to be an essential member of a diverse team of visionaries dedicated to making a lasting impact. Don’t pass up this opportunity to collaborate with some of the brightest minds in the field and deliver best-in-class solutions to the industry. As a Senior Lead Data Architect at JPMorganChase within Consumer & Community Banking, Infrastructure & Architecture Team, you are an integral part of a team that works to develop high-quality data architecture solutions for various software applications and platform products. Drive significant business impact and help shape the global target state architecture through your capabilities in multiple data architecture domains.

Requirements

Formal training or certification on data architecture concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data architecture workflows with strong validation habits and awareness of data sensitivity
Ability to assess and validate AI-assisted data architecture recommendations before adoption, escalating uncertainty and ensuring outcomes align to resiliency, security, and auditability expectations
Advanced in one or more programming language(s), applications, and architecture, with advanced knowledge of architecture, applications, and technical processes within one or more technical disciplines (e.g., Cloud, AI/ML, mobile, etc.)
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
Experience defining enterprise Data + Agentic AI platform and reference architecture spanning ingestion, curated data products, metadata/lineage, enterprise knowledge bases (vector search/RAG), agent toolchains (planning/execution), guardrails, access controls/risk controls, and evaluation/observability
Strong communication and collaboration skills to work effectively with cross-functional teams
Proven track record of delivering high-quality data architecture solutions in complex environments
Familiarity with data governance, security, and compliance standards

Nice To Haves

Experience in financial services or regulated industries
Master’s degree in a relevant field
Familiarity with data governance, security, and compliance standards
Experience with agile methodologies
Certification in cloud or data architecture
Knowledge of machine learning and advanced analytics
Published work or presentations in data architecture

Responsibilities

Represents the data architecture team at technical governance bodies, providing feedback and proposing improvements to data architecture governance practices and guiding evaluation of current and new technology using existing data architecture standards and frameworks
Uses enterprise-authorized AI capabilities within the work environment to accelerate data architecture analysis and decisioning (e.g., option evaluation and documentation), validating outputs and handling data according to sensitivity and security requirements
Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors and serves as a function-wide subject matter expert in one or more areas of focus
Develops secure and high-quality production code and reviews and debugs code written by others
Drives data architecture decisions that impact product design, application functionality and technical operations and processes
Actively contributes to the engineering community as an advocate of firmwide data frameworks, tools, and practices in the Software Development Life Cycle
Influences peers and project decision-makers to consider the use and application of leading-edge technologies
Leads reuse-first adoption of AI-assisted data validation within SDLC/toolchain routines, improving quality checks and operational stability with traceability/auditability and resiliency expectations
Defines enterprise Data + Agentic AI platform and reference architecture spanning ingestion, curated data products, metadata/lineage, enterprise knowledge bases (vector search/RAG), agent toolchains (planning/execution), guardrails, access controls/risk controls, and evaluation/observability
Guides the implementation of enterprise data solutions, ensuring alignment with business goals and compliance requirements
Collaborates with cross-functional teams to drive innovation and continuous improvement in data architecture