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

JPMorgan Chase
Houston, USA
Full-time
Lead · 5+ years experience
Onsite
Discovered 1 weeks ago
awsdatabricksjavapythonsql

Full Job Posting

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 service s 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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