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# Software Engineer [Multiple Positions Available]

- **Company:** JPMorgan Chase & Co.
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $186,160.0 - $215,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Systems, Software Debugging, Github, Apache JMeter, Machine Learning, Software Engineering, Data Streaming, Datadog, Data Processing, Cloud Platform System, Grafana, Software Application Programming, AWS Lambda, Git, Information Technology, AWS Glue, Data Analytics, Apache Kafka, Machine Learning Operations, Cloudwatch, Splunk, Software Version Control, Data Pipelines, Jenkins
- **Published:** August 25, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210782005

## About the Role

Minimum education and experience required: Bachelor's degree in Information Technology, Computer Science, Data Analytics or related field of study plus 7 years of experience in the job offered or as Software Engineer, Technical Lead, IT Consultant, or related occupation.

Skills Required: This position requires five (5) years of experience with the following: Developing applications using Java and Python; Building, deploying, and maintaining enterprise grade data solutions at scale on AWS; Delivering system design, application development, testing, and operational stability using Agile methodologies; Delivering CI/CD processes using Jenkins, AWS Pipelines, GitHub Actions, and version control systems such as Git; Designing and implementing data ingestion pipelines to stream datasets into the cloud data platform using Kafka or Kinesis; Building and managing ETL pipelines; Storing, computing, and orchestrating data using AWS cloud services including S3 for storage, AWS Lambda for event processing, AWS Glue for extract, transform, load and cataloging, and Amazon EC2 for custom or resource intensive processing; Implementing quality controls and troubleshooting issues to maintain data integrity and performance using tools such as Splunk, Grafana, Datadog, AWS
CloudWatch, or JMeter.

## Description

Duties: Design and implement scalable data processing, analytics, and machine learning workflows. Build and manage ETL and data ingestion pipelines to bring diverse datasets into the cloud while maintaining data quality and consistency. Build, optimize, and maintain scalable data infrastructure and cloud-native pipelines to ensure data is clean, reliable, and prepared for Al, machine learning, and analytics. Oversee end-to-end data flow, integration, transformation, and storage while implementing quality controls and troubleshooting to ensure data integrity and performance. Perform data modeling and exploratory data analysis to prepare and analyze data for machine learning solutions and deploy machine learning models. Create dashboards and visualizations to support data-driven decision-making and transform raw data into actionable insights. Maintain product backlogs and document processes to support strategic and operational needs. Collaborate with stakeholders including data scientists,
analysts, product managers, and engineering teams to gather requirements, deliver solutions, and communicate project status and risks. Develop, review, and debug code.


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