below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$142,450–$221,000.
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As a Lead Software Engineer - Metrics and Payments Business Observability within the Commercial & Investment Banking – Data Analytics and Payments Technology team, you will serve as a core technical contributor. You will design, build, and maintain scalable data pipelines and ETL/ELT workflows for batch and real-time processing. Your daily responsibilities include developing data platform components like data cataloging and quality frameworks, implementing data modeling strategies, and upholding engineering standards for Spring Boot services. You will utilize Python, Java, SQL, Spark, Flink, Kafka, Airflow, and AWS to solve complex data processing and ingestion problems. The role focuses on providing robust, fault-tolerant observability for metrics and payments, ensuring production readiness through automated incident response, secure coding practices, and the adoption of enterprise-authorized AI-assisted engineering tools.
Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Spark, Airflow, Kafka, and Flink.
Develop data platform components including data cataloging, quality frameworks, and semantic layers with embedded governance.
Implement data modeling strategies such as fact, dimensional, and wide tables to support analytics and reporting.
Set and uphold engineering standards for Spring Boot services, including API design, security, and performance tuning.
Ensure production readiness through observability, metrics, tracing, alerting, and proactive incident response.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
Identify and automate the remediation of recurring issues to improve the operational stability of software systems.
Lead evaluation sessions with external vendors and internal teams to probe architectural designs and technical credentials.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on experience in system design, application development, testing, and operational stability for software engineering or data platform development.
Advanced proficiency in Python, Java, and SQL.
Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink.
Experience designing and operating data pipelines on Databricks using Apache Airflow.
Experience with AWS cloud platforms, including deploying and operating services in a cloud environment.
Demonstrated experience leading the use of approved AI-assisted software development tools and understanding responsible AI use.
Advanced understanding of agile methodologies, CI/CD, application resiliency, and security.
Experience with Agentic AI, LLMs, RAG architectures, vector databases, and embedding-based retrieval systems (preferred).
Proficiency with Infrastructure as Code (Terraform) and containerized deployments (Docker, Kubernetes) (preferred).
Experience with data modeling techniques (star schema, snowflake), query optimization, and Clickhouse (preferred).
Remote (Louisville, KY)+411 days ago
$129,300–$177,800
open telemetry
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