Lead Software Engineer - Python, AWS Engineer

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Data and Analytics - Core Data Engineering services team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market‑leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Designs, implements, and maintains continuous integration and continuous deployment (CI/CD) pipelines using tools like Jenkins, Git Lab, or Terraform.
• Automates infrastructure provisioning and management using container orchestration tools such as ECS, Kubernetes, and Docker.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Monitors system performance and implement optimizations to improve efficiency and scalability.
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s) :
  Python, Java/Spring Boot
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Experience with monitoring and logging tools such as Grafana, Dynatrace, Datadog, and Splunk.
• Proficiency in CI/CD tools like Jenkins, Git Lab, or Terraform.
• Experience with container orchestration tools such as ECS, Kubernetes, and Docker.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Practical cloud native experience

• Knowledge of ML Ops practices and tools is preferred.
• Knowledge of Databricks APIs and services are preferred