Enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way for JPMorgan Chase's Chief Data & Analytics Office.
Requirements
- Formal training or certification on Software Engineering concepts and 5+ years applied experience
- Proficiency in Java (core & EE, Spring Framework)
- Practical cloud native experience in AWS
- Notable experience with cloud-based data platforms and patterns for compute, storage, analytics, and data science use cases
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Ability to tackle design and functionality problems independently with little to no oversight
- Proficiency in Python, JavaScript, or React
Responsibilities
- Executes creative software solutions, designs, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
Other
- Manages and oversees a team of employees
- Excellent verbal and written communication skills to work effectively with cross-functional teams and stakeholders
- Strong understanding of OOP & SOA principles, design patterns, industry best practices
- Experience with event-driven architectures and tools, data mesh architecture, data ingestion pipelines, ETL tools, workflow orchestration, containerization
- Ability to drive requirement refinement with product and stakeholders
