What are the responsibilities and job description for the Lead Software Engineer -Java, Python, Pyspark position at JPMorgan Chase?
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As a Lead Software Engineer at JPMorgan Chase within the COMMERCIAL & INVESTMENT BANK - Merchant service Funding team, you play a vital role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products in a secure, stable, and scalable manner. As a key technical contributor, you will be responsible for implementing essential technology solutions across diverse technical domains within various business functions, all in support of the firm's strategic objectives.
Job responsibilities
- 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
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- 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
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- 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
- Proficiency in Java, Spring Boot, Python, and cloud platforms like AWS.
- Utilize cloud-native technologies such as AWS, Kubernetes (K8s), EKS, and ECS to build and deploy applications.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Familiarity with data processing frameworks like PySpark and messaging systems like Kafka.
- Strong understanding of relational databases, particularly PostgreSQL and RDS.
- 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.)
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience