Lead Software Engineer, Metrics & Payments Platform

JPMorgan Chase; Jersey City (NJ); Presencial; USD 140 000 - 190 000; Tempo integral

Resumo da oferta

JPMorgan Chase is seeking a Lead Software Engineer - Metrics and Payments Business Observability in Jersey City. You will design and scale data pipelines, implement governance and observability, and lead AI-assisted engineering practices to improve delivery and security.

You will collaborate with analytics, product, and business stakeholders to translate requirements into production-grade solutions, uphold API standards, and ensure production readiness across services in a high‑impact

Qualificações

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability and demonstrated professional experience focused on software engineering or data platform development.
• Advanced in one or more programming languages (Python, Java, and SQL).
• Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink.
• Solid understanding of building highly scalable, robust and fault-tolerant API (REST, GraphQL).
• Experience designing and operating data pipelines on Databricks using orchestration tools such as Apache Airflow.
• Experience with AWS cloud platforms, including deploying and operating services in a cloud environment.
• Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (cloud, AI, ML, mobile, etc.)

Responsabilidades

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine approaches.
• Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows using Spark, Airflow, Kafka, and Flink.
• Develops data platform components including data cataloging, data quality frameworks, and semantic/metrics layers with governance, lineage, and compliance.
• Implements data modeling strategies to support analytics and reporting.
• Partners with analytics teams, product managers, and stakeholders to translate data requirements into production-grade solutions.
• Sets and upholds engineering standards for Spring Boot services (API design, error handling, security, logging, performance).
• Ensures production readiness through observability, alerting, incident response runbooks, and secure high-quality production code.
• Applies SDLC toolchains to improve value realized by automation, including AI-assisted development tools.
• Drives adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Identifies opportunities to automate remediation of recurring issues to improve stability.
• Leads evaluation sessions with external vendors and internal teams to assess architectural designs and applicability.

Conhecimentos

Python

Java

SQL

Apache Spark

Apache Flink

Apache Airflow

REST API

GraphQL

AWS

CI/CD

Security

Observability

Formação académica

Formal training or certification in software engineering

Ferramentas

Databricks

Terraform

AWS

Descrição da oferta de emprego

JPMorgan Chase is seeking a Lead Software Engineer - Metrics and Payments Business Observability in Jersey City. You will design and scale data pipelines, implement governance and observability, and lead AI-assisted engineering practices to improve delivery and security.

You will collaborate with analytics, product, and business stakeholders to translate requirements into production-grade solutions, uphold API standards, and ensure production readiness across services in a high‑impact