Lead Software Engineer - Lead Data Architect
JPMorgan Chase & Co. (company site, opens in a new tab)10+ yrsMumbaiOn-siteDirect career pageEst. 35–60 LPA
Posted on 31 Aug
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at JPMorgan Chase & Co.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at JPMorgan Chase & Co. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Drive end-to-end architecture and technology strategy for complex, distributed, high-throughput data and software systems across the portfolio.
- Lead design reviews, architecture governance, and set enterprise-wide patterns and standards involving senior leadership and multiple functions.
- Architect cloud-native AWS solutions including AI/ML and GenAI integration with operational rigor for performance, security, and cost management.
Minimum Requirements
- Bachelor's degree in Computer Science, IT, or Software Engineering (or equivalent).
- 10+ years of applied experience spanning data architecture and software development.
- Deep expertise in data architecture covering relational (Oracle, PostgreSQL) and NoSQL (Cassandra, MongoDB) databases and large-scale data platforms.
- Proven experience with AWS production workloads, Java or equivalent languages, microservices, streaming architectures, AI/ML and GenAI integration, and use of AI-assisted development tools.
Ideal Candidate Profile
- Experienced leader in data and software architecture driving strategic technology decisions in complex, regulated environments.
- Strong architectural mindset balancing speed, risk, maintainability, and total cost, with demonstrated DevOps and platform engineering expertise.
- Hands-on with emerging AI-assisted engineering practices and responsible AI adoption, with ability to lead senior technical talent and align across cross-functional teams.