Manager of Software Engineering - Spark, AWS, Databricks, Java

JPMorgan Chase & Co.; Wilmington (DE); On-site; USD 170,000 - 210,000; Full time

Job summary

JPMorganChase is seeking a Manager of Software Engineering within Enterprise Technology to lead multiple teams and guide day-to-day execution, ensuring compliance, business requirements, and best practices across delivery.

You will mentor engineers, set team goals, and drive adoption of AI-assisted development and SDLC automation to improve speed, quality, and resilience across platforms.

Qualifications

• Formal training or certification in software engineering with 5+ years of hands-on experience.
• Experience leading technology projects with Big Data & Event Driven Architecture.
• Hands-on experience with Spark, Databricks, AWS and Java.
• Experience managing technologists.
• Ability to promote responsible AI practices and governance in engineering workflows.
• Strong understanding of SDLC, Agile methodologies, CI/CD, security and resiliency.
• In-depth knowledge of the financial services industry IT systems.
• Practical cloud native experience.

Responsibilities

• Provides guidance to the immediate team of software engineers on daily tasks and activities.
• Sets overall guidance and expectations for team output, practices, and collaboration.
• Leads team adoption of enterprise‑authorized AI‑assisted engineering practices and SDLC/TLM automation to improve delivery speed and quality.
• Applies knowledge of the SDLC toolchain to improve value of automation and capacity unlock initiatives.
• Anticipates dependencies with other teams to deliver products and applications per business requirements.
• Manages stakeholder relationships and the team’s work in line with compliance standards, SLAs and business needs.

Skills

Leadership

Coaching & mentoring

Team ownership

Agile / CI/CD

Compliance & governance

SDLC knowledge

Stakeholder management

Risk awareness

Education

Software engineering certification

Tools

Spark & Databricks

AWS

Java

Big Data & EDA

Job description

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of Software Engineering at JPMorganChase within the Enterprise Technology, you 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
• Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives.
• 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

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 with Big Data & Event Driven Architecture.
• Experience & hands on with technology: Spark, Databricks, AWS, Java
• Experience managing technologists
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
• 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

Preferred qualifications, capabilities, and skills

• Exposure to any of decision engines like ODM, Drools