Manager of Software Engineering - Data Analytics

This role is a challenge with big impact, but you were made for this. Bring your Engineering skills and lead and manage multiple technical teams and move financial technologies forward. As a Manager of Software Engineering at JPMorgan Chase within the Corporate - Data and Analytics team, where you will lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices. Job responsibilities Provides guidance to immediate team of software engineers on daily tasks and activities Sets the overall guidance and expectations for team output, practices, and collaboration Anticipates dependencies with other teams to deliver products and applications in line with business requirements Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements Creates a culture of opportunity, inclusion, and respect for team members and prioritizes diverse representation Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience Experience leading technology projects Experience managing technologists Proficient in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Experience working at code level Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs. Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns. Preferred qualifications, capabilities, and skills Experience working with Java Springboot, Python, PiSpark, Mongodb, Oracle, Unix Experience working with AI – generative or agentic and using them in design and coding.