Senior Lead Software Engineer - Java / Python - Risk Technology Data Strategy

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Corporate Sector

Senior Lead Software Engineer focused on data engineering and software development for risk technology at JPMorgan Chase. The role involves designing, building, and enhancing data engineering solutions, ensuring secure, stable, and scalable technology products. Responsibilities include executing software solutions, developing production code, leading evaluation sessions, and driving communities of practice. Requires proficiency in engineering, architecture, and AI/ML with experience in large-scale enterprise data platforms, programming languages like Java/Python, databases, data processing, microservices, and cloud-native practices.

What you'd actually do

  1. Execute creative software solutions, design, development, and technical troubleshooting to solve complex problems
  2. Develop secure, high-quality production code for data-intensive applications and review code written by others
  3. Identify opportunities to automate remediation of recurring issues and improve operational stability
  4. Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials
  5. Drive communities of practice across Software Engineering to promote new and leading-edge technologies

Skills

Required

  • Engineering & Architecture
  • AI/ML
  • Java
  • Python
  • C/C++
  • C#
  • system design
  • application development
  • testing
  • operational stability
  • relational databases
  • NoSQL databases
  • data lake architectures
  • database querying languages
  • large-scale data processing
  • microservices
  • API design
  • Kafka
  • Redis
  • MemCached
  • Observability tools (Dynatrace, Splunk, Grafana)
  • Orchestration tools (Airflow, Temporal)
  • automation
  • continuous delivery methods
  • Software Development Life Cycle
  • agile methodologies
  • CI/CD
  • application resiliency
  • security
  • cloud-native experience

Nice to have

  • Databricks
  • Snowflake
  • Spark/PySpark
  • big data processing technologies
  • cloud
  • artificial intelligence
  • machine learning
  • mobile
  • financial services industry
  • IT systems

What the JD emphasized

  • large-scale enterprise data platforms
  • large-scale data processing