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 Technology Division, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities :
- Manage data integration and data analysis of disparate systems
- Build extensible data acquisition and integration solutions to meet the functional and non-functional requirements of the client
- Implement processes and logic to extract, transform, and distribute data across one or more data stores from a wide variety of sources
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs
- Interface with other internal product development teams as well as cross functional teams (Product Management, Integration Engineering, Quality Engineering, System Admin Teams)
- Working with remote and geographically distributed teams to enable building the right products, using the right building blocks, and making them consumable by other products easily
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands on experience in data integration projects using Big Data Technologies
- Hands on experience with a minimum of 5 years on Spark and Scala along with experience on building streaming applications using Kafka
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Strong experience in CICD using Jenkins, Git, Artifactory, Yaml, Maven for Cloud deployments
- Java opensource, API, JUnits, Spring Boot applications, Swagger Setup
- Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala- Strong experience in integrating data from different types of file-storage formats like Parquet, ORC, Avro, Sequence files etc.
- Strong technical understanding in building scalable, high performance distributed services/systems
- Strong knowledge of Data Warehousing and Data Lake concepts ; Possesses strong problem solving, troubleshooting, and analytical skills
- Having excellent communication, presentation, interpersonal, and analytical skills including the ability to communicate complex concepts clearly to different audiences
Experience in technologies like Oracle/SQL and NoSQL data stores such as DynamoDB
Preferred qualifications, capabilities, and skills:
- Experience in AWS Data Warehousing and database platforms preferred
- Ability to quickly learn new technologies in a dynamic environment
- Experience in managing team of at least 5-10 engineers.
- Big data experience preferably related to human resources analytics