JC
JPMorgan Chase
Data Engineer

Lead Software Engineer - Data Engineer [AWS, SQL, Python/Java]

On-siteSeniorData EngineerJust posted
✦Role summaryAI-generated

The Lead Software Engineer will design and implement secure, high‑performance data solutions on AWS using Python and Java, collaborating within an agile team to deliver scalable products. They will also mentor team members, enforce best coding practices, and drive adoption of enterprise‑wide data engineering standards.

Skills required

About this role

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 Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology 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.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • 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.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Strong experience in Data Engineering, Python, SQL, AWS Tech Stack
  • Strong hands-on Python/Java development experience, with the ability to design, build, and support production-grade applications and data pipelines.
  • Strong SQL skills and experience working with data processing and data engineering workloads.
  • Hands-on experience with AWS cloud services and building cloud-native solutions.
  • Strong experience with Databricks, including development and processing of large datasets.
  • Solid software engineering fundamentals, with experience delivering and supporting solutions in a production environment.
  • 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

Preferred qualifications, capabilities, and skills

  • Proficiency in automation and continuous delivery methods; strong SDLC discipline (CI/CD, testing, code quality, release controls)
  • Advanced understanding of agile delivery, application resiliency, and secure engineering practices
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