Lead data architecture strategy across a portfolio of products and applications
Drive firmwide adoption of data architecture specifications and lead a governance body
Translate complex technical issues and trends into decisions for senior leaders
Create durable, reusable data frameworks using new technology
Set guardrails for AI-assisted and agentic workflows in data architecture delivery
From the employer’s posting
Advises and leads on data architecture strategy and development of multiple products, applications, and technologies across a portfolio
Drives firmwide adoption and implementation of data architecture specifications in technology solutions and establishes and leads a data architecture governance body
Translates highly complex technical issues, trends, and approaches to leadership to drive the firm’s innovation and enable leaders to make strategic, well-informed decisions about data architecture for the target state.
Creates durable, reusable data frameworks using new technology to meet the needs of the business
Establishes portfolio-level guardrails for AI-assisted and agentic workflows used in data architecture governance and delivery
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
As a Senior Principal Data Architect at JPMorganChase within the IAM - Data Services Organization, you provide specialized expertise to influence the target state architecture and strategy. Work across teams to implement and advance the adoption of complex, strategic, global data architecture solutions that will give JPMorganChase a competitive advantage.
This is your moment to make a difference and advance the strategic direction of technology on a global scale. Your unique perspective is the perfect fit for this forward-thinking team of architects.
Job responsibilities
Advises and leads on data architecture strategy and development of multiple products, applications, and technologies across a portfolio
Leads reuse-first adoption of enterprise-authorized AI capabilities within the work environment to accelerate data architecture analysis, portfolio-level option evaluation, and delivery of strategic global solutions, with human-in-the-loop validation and appropriate handling of sensitive data.
Translates highly complex technical issues, trends, and approaches to leadership to drive the firm’s innovation and enable leaders to make strategic, well-informed decisions about data architecture for the target state.
Drives firmwide adoption and implementation of data architecture specifications in technology solutions and establishes and leads a data architecture governance body
Creates durable, reusable data frameworks using new technology to meet the needs of the business
Establishes portfolio-level guardrails for AI-assisted and agentic workflows used in data architecture governance and delivery, including traceability/auditability and control expectations aligned to resiliency and security standards.
Required qualifications, capabilities, and skills
Practical experience delivering system design, application development, testing, and operational stability, including extensive practical cloud native experience
Proven track record setting data modeling standards and influencing multiple teams/products.
Deep expertise in graph data modeling (entity/relationship design, identity resolution patterns, temporal modeling, constraint design).
Demonstrated experience leading safe adoption of enterprise-authorized AI capabilities within the work environment across data architecture workflows, including validation practices and awareness of data sensitivity.
Ability to evaluate and govern AI-enabled data architecture patterns (including agentic workflows) with clear control boundaries, auditability, and human approval checkpoints aligned to resiliency and security expectations.
Ability to evaluate current and emerging technologies to recommend the best data architecture solutions or approach to achieve the future state architecture
Preferred qualifications, capabilities, and skills
Hands-on experience with graph technologies and query languages and/or ontology frameworks
Experience with metadata management, data governance, MDM, and lineage/provenance implementations.
Familiarity with AI/ML enablement via graphs (feature generation, embeddings, relationship-aware retrieval), with strong grounding in data controls.