Big Data AWS Sr Manager of Software Engineering
JPMorgan Chase · Columbus, United States · 16h ago
SeniorOn-siteData & Analytics
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.
As a Senior Manager of Software Engineering at JPMorganChase within the Consumer & Community Banking Digital Technology team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
As a Senior Manager of Software Engineering at JPMorganChase within the Consumer & Community Banking Digital Technology team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
- Manage platform strategy and modernization (cloud-first, data-first), including AI enablement for efficiency, anomaly detection, and automation of controls.
- Champion engineering best practices for stream processing (Flink), microservices (Java/Python), API design, CI/CD, observability, and resiliency
- Leads design of high-throughput, low-latency applications leveraging state-of-the-art machine learning architectures deployed on AWS
- Designs and develops secure, scalable microservices, and reviews and debugs code written by others
- 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
- Executes creative software solutions across design, development, and technical troubleshooting, thinking beyond routine approaches to break down complex problem
- Manage a team of 8-10 varying levels of Software Engineers in a matrix environment
- Creates architecture and design artifacts for complex components and platform capabilities
- Develops secure, high-quality production code and contributes to engineering best practices across the SDLC
- Designs and implements near real-time streaming and event-driven processing using technologies such as Kafka, Kinesis, and Flink
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience . In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
- Strong management experience in a matrixed management environment
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Experience building highly scalable Java based microservices-based applications
- 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.
- Practical cloud-native experience on AWS, including building high-throughput services using EKS, ECS/Fargate and S3
- Hands-on experience in high-throughput, near real-time stream processing using Kafka, Kinesis, and Flink (on ECS/EKS where applicable)
- Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security best practices
- Proficiency with source code control systems such as Git, Bitbucket, or SVN
- Demonstrated proficiency in software applications and technical processes in one or more disciplines (e.g., cloud, AI/ML)
Preferred qualifications, capabilities, and skills
- Hands-on experience in high-volume Flink processing
- Experience with development/build tools and frameworks such as IntelliJ/Eclipse, Maven, Gradle, Spring Boot, Spring MVC and Spring Cloud
- Experience with recommendation and personalization systems
- Interest in and/or experience solving problems in the financial services domain