This listing doesn't post a salary. Most similar roles pay
$192,050–$211,200.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As an AWS Lead Software Engineer-Big Data/ETL within the Model Delivery and Platform Engineering team, you will serve as a core technical contributor in an agile environment. You will design, code, and test automation solutions, including LLMs and agents, to eliminate manual operational work while managing application risk, security, and data accountability. Your daily responsibilities involve running resilient production services, implementing monitoring and anomaly detection, and driving the adoption of AI-assisted engineering practices to improve code quality and delivery speed. You will build scalable data processing and Big Data/ETL pipelines using Java, Python, AWS, Docker, and Kubernetes. The role requires expertise in site reliability engineering, infrastructure components like load balancers and networks, and monitoring tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk to ensure stable, secure, and scalable technology products.
Design, code, and deliver automation including LLMs to eliminate manual operational work and streamline remediation workflows.
Manage application risk, compliance, and security by ensuring proper authentication, data classification, and certificate hygiene.
Build and maintain scalable Big Data and ETL pipelines using AWS and container orchestration platforms.
Operate production services end-to-end by implementing monitoring, logging, anomaly detection, and incident management protocols.
Drive the adoption of AI-assisted engineering practices to improve code quality, delivery speed, and automated testing.
Implement Site Reliability Engineering (SRE) practices using data-driven analytics to improve service levels and stability.
Coordinate across large developer communities to prioritize execution and align technical goals for high-priority workstreams.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Proven track record designing, coding, testing, and delivering production-grade software in at least one technology stack.
Advanced development experience in Java or Python with excellent debugging and troubleshooting skills for complex issues.
Hands-on experience with AWS or other clouds and container platforms/orchestration like Docker, Kubernetes, or ECS.
Experience building scalable data processing and Big Data/ETL pipelines using Hortonworks or AWS-based solutions.
Working knowledge of core infrastructure including routers, load balancers, compute, storage, networks, and cloud products.
Proficiency in SRE practices, performance, security, enterprise architecture, and monitoring tools like Grafana, Dynatrace, Prometheus, Datadog, or Splunk.
Experience with AI-assisted software development tools and understanding of responsible AI use in engineering workflows.
Java
AWS
CI/CD
Agile
Full Stack
Software Development Life Cycle
Artificial Intelligence
Machine Learning
Automated Testing
System Design
Cloud-native Engineering