Job Description

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 Infrastructure Platforms 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.

Job responsibilities

Develop and maintain applications using Apache Spark and Java Work with different aspects of spark echo system including Datasets, Spark SQL and Scalability support Work with business analysts and lead engineers to understand requirements and designs for implementing software solutions Work on performance improvement activities to support spark applications to process millions of data elements everyday Provide production support and troubleshooting activities to uncover the issues in the spark applications Contributes to software engineering communities of practice and events that explore new and emerging technologies

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 3+ years applied experience Work experience on Data Engineering domain Hands-on practical experience in system design (simple), application development, testing, and operational stability Proficient in coding in one or more languages including Java Experience in developing, debugging, and maintaining code in a corporate environment with Java, Spark Framework and Database querying languages (any SQL usage experience) Overall knowledge of the Software Development Life Cycle Experience working in an Agile Software Development Environment Lead design and team in solutioning.

Preferred qualifications, capabilities, and skills

* Exposure to cloud technologies such as AWS, Kubernetes and Kafka