Lead Data Platform Engineer – AI-Driven & Secure

JPMorgan Chase & Co.; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Job summary

JPMorgan Chase & Co. in London invites a Lead Software Engineer to design, build, and scale data engineering solutions within Corporate Risk Technology.

You will guide cross-functional teams, implement secure production code, and drive AI-assisted development practices to improve quality and speed. The role emphasizes applying cloud-native architectures, modern data technologies like Kafka, Databricks, and Spark, and maintaining operational stability while shaping the team's technical strategy

Qualifications

• Proficiency in engineering & architecture concepts for large-scale data platforms.
• Hands-on experience with AI/ML in engineering workflows and secure coding practices.
• Strong in Java, Python, C/C++, or C# with production-grade delivery.
• Experience with relational/NoSQL databases, data lakes, and data processing pipelines.

Responsibilities

• Execute creative software solutions and troubleshoot complex problems.
• Develop secure, production-grade data-intensive code and review peers' work.
• Identify automation opportunities to improve stability and reduce toil.
• Lead evaluation sessions with vendors and internal teams on architectures.
• Promote AI-assisted engineering practices to improve quality, speed, and reliability across teams.
• Apply SDLC tooling knowledge to improve automation and governance across workflows.
• Foster communities of practice and a culture of diversity and inclusion.

Skills

Engineering & Architecture

AI/ML

Java

Python

C/C++

CI/CD

Cloud-native

Microservices

Kafka

Observability

APIs design

Security & resiliency

Leadership/mentoring

Tools

Databricks

Snowflake

Spark

PySpark

Airflow

Temporal

Job description

JPMorgan Chase & Co. in London invites a Lead Software Engineer to design, build, and scale data engineering solutions within Corporate Risk Technology.

You will guide cross-functional teams, implement secure production code, and drive AI-assisted development practices to improve quality and speed. The role emphasizes applying cloud-native architectures, modern data technologies like Kafka, Databricks, and Spark, and maintaining operational stability while shaping the team's technical strategy