JPMorgan Lead Software Engineer UI Data Engineering 

United States, Texas, Plano 

397840813

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 internaland externalteams 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, equity, inclusion, and respect

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Proficiency 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
• 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

• Proficient in building UI using JavaScript, ReactJS, UI unit testing frameworks, knowledge on using 1 or more charts, data grid libraries, building modularized UI components
• Proficient in designing optimal data models that operates effectively pivot/window/aggregation/time-series functions
• Proficient in data engineering concepts to build high performing ETL pipeline, Transformers that works with large volume datasets using distributed computing like Spark
• Proficient in Python and libraries typically used for data engineering use cases