Senior Software Engineer - Metrics & Payments Platform

Aumni; Austin (TX); Hybrid; USD 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer - Metrics and Payments Business Observability in Austin, TX.

You will lead design, development, and operations of data pipelines, analytics platforms, and production-grade services to support payments and observability with strong governance and security. You will collaborate with product managers and stakeholders to translate data needs into scalable, reliable solutions, while advancing AI-assisted tooling and secure coding practices

Qualifications

• Formal training or certification on software engineering concepts and 5+ years of applied experience.

Responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting.
• Builds and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing with Spark, Airflow, Kafka, and Flink.
• Develops data platform components with governance, lineage, and compliance standards.
• Implements data modeling strategies to support analytics and reporting.
• Collaborates with analytics teams and stakeholders to translate data requirements into production solutions.
• Sets engineering standards for Spring Boot services (API design, security, logging, performance).
• Ensures production readiness through observability, alerting, incident response, and secure high-quality production code.

Skills

Python

Java

SQL

Spark

Flink

Airflow

Databricks

REST APIs

GraphQL

AWS

Terraform

Docker

Kubernetes

Tools

Kafka

Job description

JPMorgan Chase & Co. is seeking a Lead Software Engineer - Metrics and Payments Business Observability in Austin, TX.

You will lead design, development, and operations of data pipelines, analytics platforms, and production-grade services to support payments and observability with strong governance and security. You will collaborate with product managers and stakeholders to translate data needs into scalable, reliable solutions, while advancing AI-assisted tooling and secure coding practices