As a Spark/AWS Software Engineer at JPMorgan Chase within the agile development team, you will contribute to the enhancement, design, and delivery of the firm's cutting-edge technology products in a secure, stable, and scalable manner. As a growing member of our software engineering team, you will be responsible for executing software solutions through the design, development, and technical troubleshooting of various components within a technical product, application, or system, all while acquiring the skills and experience necessary for professional growth.
Job Responsibilities:
- Execute standard software solutions, design, development, and technical troubleshooting.
- Write secure, high-quality code in at least one programming language with limited guidance.
- Design, develop, code, and troubleshoot while considering upstream and downstream systems.
- Apply knowledge of Software Development Life Cycle tools to enhance automation value.
- Use technical troubleshooting to solve basic complexity technical problems.
- Gather, analyze, and interpret large data sets to identify problems and aid decision-making.
- Learn and apply system processes and methodologies for developing secure, stable code and systems.
- Required Qualifications, Capabilities, and Skills:
- Formal training or certification in software engineering concepts with 3+ years of applied experience.
- Proficiency with distributed computing frameworks like Apache Spark, particularly Java/Spark.
- Experience building data pipelines on AWS using Lambda, SQS, SNS, Athena, Glue, and EMR.
- Proficient in coding, preferably in Java Spark.
- Experience writing SQL queries.
- Experience in system design, application development, testing, and operational stability.
- Experience in developing, debugging, and maintaining code in a corporate environment.
- Understanding of the Software Development Life Cycle and agile methodologies like CI/CD, application resiliency, and security.
Preferred qualifications, capabilities, and skills
- Good knowledge on Cloud technology