The role
From JPMorgan Chase's own posting.
Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.
As a Data Engineer III at JPMorganChase within the Consumer & Community Banking - Wealth Management team, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Design and develop responsive, user-friendly UI components and workflows.
Build and maintain experience services (API/service layer supporting front-end experiences), primarily using Java .
Implement and integrate agentic capabilities (e.g., workflow orchestration, tool/function calling patterns, guardrails, state management for agent flows) into applications and user journeys.
Collaborate with product, design, and backend teams to translate requirements into reliable, performant solutions.
Debug issues across UI and services; use basic SQL queries to validate data, investigate defects, and support root-cause analysis.
Ensure code quality through reviews, testing, documentation, and adherence to engineering standards.
Required qualifications, capabilities, and skills
Formal training or certification on data engineering concepts and 3+ years applied experience
UI development (building production-grade user interfaces)
Experience services development (building services/APIs supporting UI experiences)
Strong hands-on experience with Java for backend/service development (e.g., building RESTful services).
Exposure to agentic capabilities / LLM-driven workflows and integrating them into applications.
Basic SQL knowledge (writing simple queries for validation and troubleshooting).
Strong problem-solving skills, communication, and ability to work in an agile environment.
Preferred qualifications, capabilities, and skills
Machine Learning exposure (foundational understanding, model integration, or ML-enabled features).
Experience with Apache Spark (batch/stream processing, data pipelines, or large-scale data processing).
Experience with API design best practices, service reliability, observability, and performance optimization.
Familiarity with secure coding practices (authentication/authorization, data handling, input validation).
Experience with CI/CD and automated testing.