Software Engineer [Multiple Positions Available]
About The Position
JPMorgan Chase is seeking a Software Engineer to design and implement scalable data processing, analytics, and machine learning workflows. This role involves building and managing ETL and data ingestion pipelines, optimizing data infrastructure, and ensuring data quality and reliability for AI, machine learning, and analytics. The engineer will perform data modeling, exploratory data analysis, and deploy machine learning models. They will also create dashboards and visualizations to provide actionable insights and maintain product backlogs and documentation. Collaboration with stakeholders such as data scientists, analysts, product managers, and engineering teams is a key aspect of this position, requiring effective communication of project status and risks. The role also includes developing, reviewing, and debugging code.
Requirements
- Bachelor's degree in Information Technology, Computer Science, Data Analytics or related field of study.
- 7 years of experience in the job offered or as Software Engineer, Technical Lead, IT Consultant, or related occupation.
- Five (5) years of experience with Developing applications using Java and Python.
- Five (5) years of experience with Building, deploying, and maintaining enterprise grade data solutions at scale on AWS.
- Five (5) years of experience with Delivering system design, application development, testing, and operational stability using Agile methodologies.
- Five (5) years of experience with Delivering CI/CD processes using Jenkins, AWS Pipelines, GitHub Actions, and version control systems such as Git.
- Five (5) years of experience with Designing and implementing data ingestion pipelines to stream datasets into the cloud data platform using Kafka or Kinesis.
- Five (5) years of experience with Building and managing ETL pipelines.
- Five (5) years of experience with 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.
- Five (5) years of experience with Implementing quality controls and troubleshooting issues to maintain data integrity and performance using tools such as Splunk, Grafana, Datadog, AWS CloudWatch, or JMeter.
Responsibilities
- 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 AI, 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.
Benefits
- Comprehensive health care coverage
- On-site health and wellness centers
- Retirement savings plan
- Backup childcare
- Tuition reimbursement
- Mental health support
- Financial coaching
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What This Job Offers
Job Type
Full-time
Career Level
Senior
