Senior Lead Architect - Data & Reporting

Job Description

Join a team where your architectural vision directly drives revenue growth, risk reduction, and merchant experience at global scale. At JPMorganChase, we invest in bold ideas and the people who bring them to life — offering you the tools, platform, and partnerships to deliver solutions that matter.

As a Senior Lead Data Architect at JPMorganChase within the Commercial & Investment Bank(Payments Technology), you are an integral part of a team that works to develop high-quality architecture solutions for data, analytics, and AI products that power Merchant Payment Services. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains — owning both platform enablement and business-facing value delivery across a highly competitive and fast-moving landscape.

Merchant Payment Services is accelerating the pace of delivery for data, analytics, and AI solutions to go to market faster and monetize near-term opportunities. This role owns a dual mandate: platform and build (Snowflake enablement, reusable capabilities, reliability, security, and controls) and business-facing value delivery (merchant and sales insights, risk and loss reduction, and operational efficiency). You will partner closely with Product, Sales, Operations, Architecture, and Risk and Controls to deliver scalable capabilities and outcomes the field can use immediately.

Job responsibilities

• Represent the Merchant Payments product family in technical governance bodies and propose improvements to architecture governance practices, including data contract and backward-compatibility standards that protect downstream consumers
• Drive Snowflake-based analytics and AI enablement with governed data products, secure access, scalable patterns, and performance and cost guardrails aligned to enterprise standards
• Define reference architectures and reusable components with engineering and platform teams, including payments-scale aggregation and merchant entity resolution patterns
• Leverage 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
• Guide evaluation of current and new technologies using existing standards and frameworks, influencing peers and decision-makers to adopt leading-edge solutions where appropriate
• Establish reuse-first, AI-enabled engineering patterns and governance across the software development lifecycle and toolchain practices, ensuring traceability, auditability, resiliency, and security controls
• Sponsor data governance across ownership and stewardship, metadata and lineage, data quality service-level agreements, retention and access controls, and dataset certification — standardizing critical metric definitions to reduce drift and reconciliation
• Drive decisions that influence product design, application functionality, and technical operations, including non-functional requirements across availability, performance, scalability, observability, and security
• Develop secure and high-quality production code, and review and debug code written by others, enforcing quality gates including static analysis, secure coding, and automated testing
• Serve as a function-wide subject matter expert and contribute to the engineering community as an advocate of firmwide software development lifecycle frameworks and practices

Required qualifications, capabilities, and skills

• Formal training or certification on architecture concepts and 5+ years applied experience
• 6+ years of hands-on practical experience delivering data architecture, reporting, and analytics solutions with practical cloud-native experience
• Advanced proficiency in one or more programming languages and deep expertise in software architecture, applications, and technical processes within one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, data platforms)
• Demonstrated experience applying enterprise-authorized AI capabilities within architecture and engineering workflows, with strong validation habits and awareness of data sensitivity
• Ability to evaluate and integrate AI-enabled capabilities into enterprise-grade architectures while meeting resiliency, security, and auditability requirements
• Strong understanding of modern data platforms and governance, including data products, metadata and lineage, data quality, and access controls
• Demonstrated engineering leadership with strong software development lifecycle discipline, including code reviews, automated testing, continuous integration and delivery, and release governance
• 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 and translate strategy into measurable outcomes across cross-functional teams

Preferred qualifications, capabilities, and skills

• Hands-on Snowflake experience for scalable analytics and AI workloads, including performance and cost optimization patterns
• Experience building and operating large language model and agentic systems with evaluation frameworks, safety controls, monitoring, and human oversight
• Experience operating high-throughput, low-latency, 24x7 platforms, with payments experience strongly preferred
• Experience in regulated environments with familiarity in merchant payments domains such as authorization performance, disputes and chargebacks, fraud and loss, onboarding, and servicing workflows
• Proven experience designing solutions for data warehousing and data lake architecture, ensuring data quality and data management processes aligned to regional compliance and controls requirements