We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer II at JPMorganChase within the Consumer and Investment Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes standard software solution, design, development, and technical troubleshooting
Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- 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
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Processing and analyzing large datasets using Big Data technologies, including Apache Spark, across data platforms comprising of Redshift, SQL DB, RDS and Databricks.
- Design, development, and implementation of scalable data pipelines and data matching solutions on AWS, utilizing Python for data engineering tasks.
- Setup and Configuration of AWS services such as S3, Databricks, Step Functions, EMR, Glue, Lambda, RDS, EventBridge, Step-Functions and API Gateway for scripting, automation, and orchestration of data workflows.
- Development of semantic layer for data consumption using Iceberg tables and APIs.
- Implementation of continuous deployment and integration processes using Infrastructure as Code tools, including Terraform.
- Apply application, data, and infrastructure architecture disciplines to optimize data-intensive applications for performance and scalability.
- Troubleshoot and resolve issues related to application code and data workflows.
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Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
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Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies