Lead Data Platform Engineer (Python/Java, AWS/Databricks)

J.P. MORGAN

Greater London

On-site

GBP 90,000 - 135,000

Full time

8 days ago

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Job summary

JPMorgan Chase | Lead Software Engineer within the Credit Data Pond team of Wholesale credit risk technology is turning ideas into trusted market-leading technology products. You will contribute across SDLC and architecture, collaborating with agile teams to deliver secure, scalable solutions for the firm's business objectives.

As a core technical contributor, you will shape design, coding, testing, and operational stability while applying enterprise AI-assisted practices and safe data handling

Qualifications

  • Formal training or certification on software engineering concepts and advanced applied experience in Python.
  • Advanced in one or more programming language(s).
  • Experience leading effective use of AI-assisted software development tools with the ability to validate AI outputs for correctness, performance, and security.
  • Defines a practical operating model for AI-assisted development with guidelines and escalation paths.

Responsibilities

  • Executes creative software solutions, design, development, and debugging with non-routine problem solving.
  • Develops secure, high-quality production code and reviews peers' code.
  • Drives enterprise AI-assisted engineering practices to improve code quality, delivery speed, and reliability.

Skills

Python
AI-assisted development
Software design & development
Security & resiliency
Agile & CI/CD
Cloud native

Tools

Jenkins
Databricks
Terraform
Delta Lake

Job description

JPMorgan Chase | Lead Software Engineer within the Credit Data Pond team of Wholesale credit risk technology is turning ideas into trusted market-leading technology products. You will contribute across SDLC and architecture, collaborating with agile teams to deliver secure, scalable solutions for the firm's business objectives.

As a core technical contributor, you will shape design, coding, testing, and operational stability while applying enterprise AI-assisted practices and safe data handling

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