Lead Software Engineer

JPMorgan Chase & Co.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A global financial services firm in Singapore is seeking a Lead Software Engineer to enhance technology products in commercial and investment banking. As a key technical contributor, you will be responsible for delivering innovative and secure solutions while leading software engineering practices. Candidates should have over 5 years of experience, hands-on programming expertise in languages such as Python and Java, as well as familiarity with AWS, containerization, and DevOps methodologies. Join a diverse and inclusive team dedicated to pushing boundaries in technology.

Qualifications

• 5+ years of applied experience in software engineering.
• Hands-on experience in system design, application development, and operational stability.
• Proficiency in automation and continuous delivery methods.

Responsibilities

• Develops secure high-quality production code and debugs code.
• Identifies opportunities to improve operational stability of software applications.
• Leads evaluation sessions with vendors to assess architectural designs.

Skills

Python

Pyspark

Java

Springboot

Pentaho

Docker

Kubernetes

AWS

DevOps CI/CD

Oracle

Education

Formal training or certification in software engineering

Tools

Control-M

Airflow

Autosys

Job description

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 Commercial and Investment Banking, 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 break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• 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
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s): Python, Pyspark, Java, Springboot, Pentaho
• Implement and manage cloud-based solutions on AWS preferable (Microservices, Postgres Database), ensuring high availability and scalability
• Hands on experience with containerization technologies such as Docker and Kubernetes
• Develop and optimize complex queries and procedures in relational database (Oracle)
• Proficiency in automation and continuous delivery methods, DevOps CI/CD pipelines (Jenkins/other frameworks)
• In-depth knowledge of the financial services industry and their IT systems
• SRE skills preferable
• Familiarity with Control‑M, Airflow, Autosys for job scheduling and automation

Preferred qualifications, capabilities and skills

• Knowledge on Databricks and DataLake house
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, etc.)
• Exposure to Production Management process like Incidents, Change Management and other relevant process knowledge