Manager of Software Engineering: Data Analytics

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference. As a

Manager of Software Engineering:

Data Analytics at JPMorganChase within the CCB Connected Commerce - Banking Payments, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives. 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and data pipelines 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 in software engineering concepts and 5+ years of applied experience Extensive experience building and operating AWS/public cloud-based applications Strong Python (Pyspark) programming skills Proven hands ‑ on delivery across system design, application development, testing, and operational stability. 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 Experience working at code level Experience with pipelines and DAGs for data processing and/or machine learning Demonstrated proficiency in cloud and AI/ML software practices Experience driving adoption of AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, with measurable productivity and quality gains Preferred qualifications, capabilities, and skills AWS (hands-on): Glue, EventBridge, Step Functions, S3,

Lambda, ECS, EKS, Kinesis, CloudWatch Outside AWS:

Python, Terraform, TigerGraph, graph databases, GitHub Copilot, Airflow, Kubernetes JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes) - For Internal to JPMC