Description This is your chance to change the path of your career and guide a team to success at one of the world's leading financial institutions. As a Lead Software Engineer at JPMorgan Chase within the Client Data Exchange Team, you are hands-on and lead a team 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 Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Contributes to software engineering communities of practice and events that explore new and emerging technologies Creates a culture of diversity, equity, inclusion, and respect for the team members and prioritizes diverse representation Required qualifications, capabilities, and skills Formal training or certification on Java programming concepts and proficient advanced experience Formal training or certification on Python programming concepts Experience leading technology projects and managing technologists Proficient in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle, agile methodologies such as CI/CD, Application Resiliency, and Security Cloud implementation experience with AWS including: AWS Data Services: Glue ETL (or) EMR, S3, Glue Catalog, Athena, Lambda Step Functions Event Bridge, ECS Data De/Serialization: Parquet and JSON format AWS Data Security: Good Understanding of security concepts such as: IAM, Service roles, Encryption, KMS, Secrets Manager Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines Exposure to big data frameworks (Spark, Hadoop etc.) used for scalable distributed processing Ability to collaborate effectively with Data Scientists to translate analytical insights into technical solutions Preferred qualifications, capabilities, and skills Familiarity with No SQL Databases such as MongoDB Experience in various messaging technologies such as Kafka Knowledge of the financial services industry and their IT systems