JP Morgan Chase

Runs a consumer bank and an investment bank

Lead Software Engineer - Data/Payments Technology

Data EngineeringConfirmed live in the last 24 hours

Full-timePlano, TX, USANo salary listedIn-person

About the Job

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
At least 10 years of software and/or data engineering experience building enterprise-scale solutions.
Practical experience delivering system design, application development, testing, and operational stability.
Advanced proficiency in one or more programming languages.
Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, and setting team expectations for validating outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption.
Hands-on experience with Databricks and distributed data processing technologies.
Strong programming and data engineering fundamentals, including experience building production-grade data solutions.
Understanding of data architecture, data modeling, data integration, and data product principles.
Experience designing and operating large-scale data platforms and data products in complex enterprise environments.
Engineering judgment and ability to troubleshoot complex technical problems independently and influence solution direction.

Responsibilities

Lead the design and development of scalable, reliable, and reusable enterprise data products.
Provide hands-on technical leadership across solution design, implementation, code reviews, troubleshooting, and production readiness.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, including AI-assisted code review and refactoring, test strategy acceleration, and incident/root-cause analysis support; establish validation standards for secure coding, peer review, and automated testing, and promote reuse of effective patterns.
Apply knowledge of software development lifecycle tools, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Establish and promote effective data engineering patterns and standards across the team.
Design solutions supporting analytical, operational, reporting, and AI-driven use cases.
Drive data quality, reliability, observability, governance, performance, and scalability across data products.
Partner with architects, product teams, engineers, and data producers and consumers to translate business needs into sustainable data solutions.
Mentor engineers and help build data engineering capability within the team.
Identify opportunities to simplify platforms, improve engineering productivity, and increase reuse.

Desired Qualifications

Experience working with modern enterprise data platforms and cloud-native data architectures.
Experience supporting real-time, analytical, or AI/ML-oriented data use cases.
Experience delivering data solutions within financial services or another highly regulated environment.
Relevant Databricks, cloud, or data engineering certification.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Global Banking Sales Enablement team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology and data products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will play a key role in building and evolving enterprise data products and strengthening our Data Engineering capabilities. This role requires a strong hands-on Data Engineer with deep experience in the Databricks ecosystem, enterprise-scale data platforms, and modern data engineering practices. You will contribute directly to solution design and implementation while providing technical leadership, establishing engineering patterns, and helping develop the broader team.

Job responsibilities

Lead the design and development of scalable, reliable, and reusable enterprise data products.
Provide hands-on technical leadership across solution design, implementation, code reviews, troubleshooting, and production readiness
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Establish and promote effective Data Engineering patterns and standards across the team.
Design solutions that support analytical, operational, reporting, and AI-driven use cases.
Drive data quality, reliability, observability, governance, performance, and scalability across data products.
Partner with architects, product teams, engineers, and data producers/consumers to translate business needs into sustainable data solutions.
Mentor engineers and help build strong Data Engineering capability within the team.
Identify opportunities to simplify platforms, improve engineering productivity, and increase reuse.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience
Minimum of 10+ years of software and/or data engineering experience building enterprise-scale solutions.
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) 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; experience coaching engineers on safe, compliant adoption within delivery practices
Deep hands-on experience with Databricks and distributed data processing technologies.
Strong programming and Data Engineering fundamentals with experience building production-grade data solutions.
Strong understanding of data architecture, data modeling, data integration, and data product principles.
Experience designing and operating large-scale data platforms and data products in complex enterprise environments.
Strong engineering judgment with the ability to independently troubleshoot complex technical problems and influence solution direction.

Preferred qualifications, capabilities, and skills

Experience working with modern enterprise data platforms and cloud-native data architectures.
Experience supporting real-time, analytical, or AI/ML-oriented data use cases.
Experience delivering data solutions within financial services or another highly regulated environment.
Relevant Databricks, Cloud, or Data Engineering certification.

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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