You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II at JPMorgan Chase as a part of Corporate and Investment Bank, 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:

Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics. Frequently utilizes SQL and understands NoSQL databases and their niche in the marketplaceCollaborate closely with cross-functional teams to develop efficient data pipelines to support various data-driven initiativesImplement best practices for data engineering, ensuring data quality, reliability, and performanceContribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflowsPerform data extraction and implement complex data transformation logic to meet business requirementsLeverage advanced analytical skills to improve data pipelines and ensure data delivery is consistent across projectsMonitor and executes data quality checks to proactively identify and address anomalies. Ensure data availability and accuracy for analytical purposesIdentify opportunities for process automation within data engineering workflowsCommunicate technical concepts to both technical and non-technical stakeholders. Deploy and manage containerized applications using Kubernetes (EKS) and Amazon ECS.Implement data orchestration and workflow automation using  AWS step , Event Bridge. Use Terraform for infrastructure provisioning and management, ensuring a robust and scalable data infrastructure.

Required qualifications, capabilities, and skills

Formal training or certification on Data Engineering concepts and 3+ years applied experience. Experience across the data lifecycleAdvanced at SQL (e.g., joins and aggregations) Advanced knowledge of RDBMS like Aurora. Experience in Microservice based component using ECS or EKS Working understanding of NoSQL databases. 4 + years of Data Engineering experience in building and optimizing data pipelines, architectures, and data sets ( Glue or Databricks etl) Proficiency in object-oriented and object function scripting languages (Python etc.)Experience in developing ETL process and workflows for streaming data from heterogeneous data sourcesWillingness and ability to learn and pick up new skillsetsExperience working with modern DataLakes: Databricks )Experience building Pipeline on AWS using Terraform and  using CI/CD piplelines 


Preferred qualifications, capabilities, and skills

Experience with data pipeline and workflow management tools (Airflow, etc.)
Strong analytical and problem-solving skills, with attention to detail.
Ability to work independently and collaboratively in a team environment.
Good communication skills, with the ability to convey technical concepts to non-technical stakeholders.
A proactive approach to learning and adapting to new technologies and methodologies.